[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"summary-580a6c1aa1d1d1d8-crystalis-coordinated-multi-view-visualization-via-summary":3,"summaries-facets-categories":79,"summary-related-580a6c1aa1d1d1d8-crystalis-coordinated-multi-view-visualization-via-summary":6497},{"id":4,"title":5,"ai":6,"body":13,"categories":46,"created_at":48,"date_modified":48,"description":40,"extension":49,"faq":48,"featured":50,"kicker_label":48,"meta":51,"navigation":63,"path":64,"published_at":65,"question":48,"scraped_at":65,"seo":66,"sitemap":67,"source_id":68,"source_name":69,"source_type":70,"source_url":56,"stem":71,"tags":72,"thumbnail_url":48,"tldr":76,"tweet":48,"unknown_tags":77,"__hash__":78},"summaries\u002Fsummaries\u002F580a6c1aa1d1d1d8-crystalis-coordinated-multi-view-visualization-via-summary.md","Crystalis: Coordinated Multi-View Visualization via Semantic Annealing",{"provider":7,"model":8,"input_tokens":9,"output_tokens":10,"processing_time_ms":11,"cost_usd":12},"openrouter","google\u002Fgemini-3.1-flash-lite",4000,459,2344,0.0016885,{"type":14,"value":15,"toc":39},"minimark",[16,21,25,29,32,36],[17,18,20],"h2",{"id":19},"the-challenge-of-multi-view-coherence","The Challenge of Multi-View Coherence",[22,23,24],"p",{},"Generating multiple, coordinated visualizations for a single dataset often leads to semantic drift, where different views (e.g., a bar chart and a scatter plot) fail to represent the same underlying data relationships or design intent. Crystalis addresses this by treating visualization generation as a crystal growth process, ensuring that individual views remain anchored to a unified semantic structure.",[17,26,28],{"id":27},"progressive-nucleation-establishing-the-semantic-core","Progressive Nucleation: Establishing the Semantic Core",[22,30,31],{},"The first stage, progressive nucleation, identifies the most salient data relationships to serve as the 'seed' for the visualization. By prioritizing high-information-density features, the model establishes a structural foundation. This prevents the generation process from drifting into arbitrary aesthetic choices that do not serve the data's analytical purpose, ensuring that every view is derived from a consistent interpretation of the dataset.",[17,33,35],{"id":34},"semantic-annealing-refining-visual-consistency","Semantic Annealing: Refining Visual Consistency",[22,37,38],{},"Once the core structure is established, the semantic annealing process iteratively refines the visualizations. Similar to physical annealing, this stage gradually reduces the 'temperature' of the generation process—moving from high-level structural exploration to precise, fine-grained visual encoding. This ensures that while each view is tailored to its specific chart type, the semantic mapping (e.g., color encoding, axis scaling, and data filtering) remains consistent across the entire dashboard. The result is a set of coordinated views that function as a cohesive analytical narrative rather than a collection of disjointed charts.",{"title":40,"searchDepth":41,"depth":41,"links":42},"",2,[43,44,45],{"id":19,"depth":41,"text":20},{"id":27,"depth":41,"text":28},{"id":34,"depth":41,"text":35},[47],"Data Science & Visualization",null,"md",false,{"content_references":52,"triage":58},[53],{"type":54,"title":55,"url":56,"context":57},"paper","Crystalis: Progressive Nucleation and Semantic Annealing for Coordinated Multi-View Visualization Generation","https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.24766","cited",{"relevance":59,"novelty":59,"quality":59,"actionability":60,"composite":61,"reasoning":62},4,3,3.8,"Category: Data Science & Visualization. The article presents a novel framework for generating coherent multi-view visualizations, addressing a specific pain point of semantic drift in data representation. While it offers insights into the methodology, it lacks detailed practical steps for implementation.",true,"\u002Fsummaries\u002F580a6c1aa1d1d1d8-crystalis-coordinated-multi-view-visualization-via-summary","2026-07-30 03:13:52",{"title":5,"description":40},{"loc":64},"580a6c1aa1d1d1d8","arXiv cs.AI","article","summaries\u002F580a6c1aa1d1d1d8-crystalis-coordinated-multi-view-visualization-via-summary",[73,74,75],"data-visualization","machine-learning","ai-llms","Crystalis introduces a two-stage framework—progressive nucleation and semantic annealing—to generate coherent, multi-view data visualizations that maintain semantic consistency across different chart types.",[75],"uRff9EoSCNp2n3nImHtzXZsDPhFmCCk3sODtFqG5zEk",[80,83,86,88,91,93,96,99,101,103,105,108,110,112,114,116,119,121,123,125,127,130,132,134,136,138,140,142,144,146,148,150,152,154,156,158,160,162,164,166,168,170,172,175,177,179,181,183,185,187,189,191,193,195,197,199,201,204,206,208,210,212,214,216,218,220,222,224,226,228,230,232,234,236,238,241,243,245,247,249,251,253,255,257,259,261,263,265,267,270,272,274,276,278,280,282,284,286,288,290,292,294,296,298,300,302,304,306,308,310,312,314,316,318,320,322,324,326,328,330,333,335,337,339,341,343,345,347,349,351,353,356,358,360,362,364,366,368,370,372,374,376,378,380,382,384,386,389,391,393,395,397,399,401,403,405,407,409,412,414,416,418,420,422,424,426,428,430,432,434,436,438,440,442,444,446,448,450,452,454,456,458,460,462,464,467,469,471,474,476,478,480,482,484,486,488,490,492,494,496,498,500,503,505,507,509,511,513,515,517,519,521,523,525,528,530,532,534,536,538,540,542,544,546,548,550,552,554,556,558,560,562,564,566,568,570,572,574,576,578,580,582,584,586,588,590,592,594,596,598,600,602,604,606,608,610,612,614,616,618,620,622,624,626,628,630,632,634,636,638,640,642,644,646,648,650,652,654,656,658,660,662,664,666,668,670,672,674,676,678,680,682,684,686,688,690,692,694,696,698,700,702,704,706,708,710,712,714,716,718,720,722,724,726,728,730,732,734,736,738,740,742,744,746,748,750,752,754,756,758,760,762,764,766,768,770,772,774,776,778,780,782,784,786,788,790,792,794,796,798,800,803,805,807,809,811,814,816,818,820,822,824,826,828,830,832,834,836,839,841,843,845,847,849,851,853,855,857,859,861,863,865,867,869,871,873,875,877,879,881,883,885,887,889,891,893,895,897,899,901,903,905,907,909,911,913,915,917,919,921,923,925,927,929,931,933,935,937,939,941,943,945,947,949,951,953,955,957,959,961,963,965,967,969,971,973,975,977,979,981,983,985,987,989,991,993,995,997,999,1001,1003,1005,1007,1009,1011,1013,1015,1017,1019,1021,1023,1025,1027,1029,1031,1033,1035,1037,1039,1041,1043,1045,1047,1049,1051,1053,1055,1057,1059,1061,1063,1065,1067,1069,1071,1073,1075,1077,1079,1081,1083,1085,1087,1089,1091,1093,1095,1097,1099,1101,1103,1105,1107,1109,1111,1113,1115,1117,1119,1121,1123,1125,1127,1129,1131,1133,1135,1138,1140,1142,1144,1146,1148,1150,1152,1154,1156,1158,1160,1162,1164,1166,1168,1170,1172,1174,1176,1178,1180,1182,1184,1186,1188,1190,1192,1194,1196,1198,1200,1202,1204,1206,1208,1210,1212,1214,1216,1218,1220,1222,1224,1226,1228,1230,1232,1234,1236,1238,1240,1242,1244,1246,1248,1250,1252,1254,1256,1258,1260,1262,1264,1266,1268,1270,1272,1274,1276,1278,1280,1282,1284,1286,1288,1290,1292,1294,1296,1298,1300,1302,1304,1306,1308,1310,1312,1314,1316,1318,1320,1322,1324,1326,1329,1331,1333,1335,1337,1339,1341,1343,1345,1347,1349,1351,1353,1355,1357,1359,1361,1363,1365,1367,1369,1371,1373,1375,1377,1379,1381,1383,1385,1387,1389,1391,1393,1395,1397,1399,1401,1403,1405,1407,1409,1411,1413,1415,1417,1419,1421,1423,1425,1427,1429,1431,1433,1435,1437,1439,1441,1443,1445,1447,1449,1451,1453,1455,1457,1459,1462,1464,1466,1468,1470,1472,1474,1476,1478,1480,1482,1484,1486,1488,1490,1492,1494,1496,1498,1500,1502,1504,1506,1508,1510,1512,1514,1516,1518,1520,1522,1524,1526,1528,1530,1532,1534,1536,1538,1540,1542,1544,1546,1548,1550,1552,1554,1556,1558,1560,1562,1564,1566,1568,1570,1572,1574,1576,1578,1580,1582,1584,1586,1588,1590,1592,1594,1596,1598,1600,1602,1604,1607,1609,1611,1613,1615,1617,1619,1621,1623,1625,1627,1629,1631,1633,1635,1637,1639,1641,1643,1645,1647,1649,1651,1653,1655,1657,1659,1661,1663,1665,1668,1670,1672,1674,1676,1678,1680,1682,1684,1686,1688,1690,1692,1694,1696,1698,1700,1702,1704,1706,1708,1710,1712,1714,1716,1718,1720,1722,1724,1726,1728,1730,1732,1734,1736,1738,1740,1742,1744,1746,1748,1750,1752,1754,1756,1758,1760,1762,1764,1766,1768,1770,1772,1774,1776,1778,1780,1782,1784,1786,1788,1790,1792,1794,1796,1798,1800,1802,1804,1806,1808,1810,1812,1814,1816,1818,1820,1822,1824,1826,1828,1830,1832,1834,1836,1838,1840,1842,1844,1846,1848,1850,1852,1854,1856,1858,1860,1862,1864,1866,1868,1870,1872,1874,1876,1878,1880,1882,1884,1886,1888,1890,1892,1894,1896,1898,1900,1902,1904,1906,1908,1910,1912,1914,1916,1918,1920,1922,1924,1926,1928,1930,1932,1934,1936,1938,1940,1942,1944,1946,1948,1950,1952,1954,1956,1958,1960,1962,1964,1966,1968,1970,1972,1974,1976,1978,1980,1982,1984,1986,1988,1990,1992,1994,1996,1998,2000,2002,2004,2006,2008,2010,2012,2014,2016,2018,2020,2022,2024,2026,2028,2030,2032,2034,2036,2038,2040,2042,2044,2046,2048,2050,2052,2054,2056,2058,2060,2062,2064,2066,2069,2071,2073,2075,2077,2079,2081,2083,2085,2087,2089,2091,2093,2095,2097,2099,2101,2103,2105,2107,2109,2111,2113,2115,2117,2119,2121,2123,2125,2127,2129,2131,2133,2135,2137,2139,2141,2143,2145,2147,2149,2152,2154,2156,2158,2160,2162,2164,2166,2168,2170,2172,2174,2176,2178,2180,2182,2184,2186,2188,2190,2192,2194,2196,2198,2200,2202,2204,2206,2208,2210,2212,2214,2216,2218,2220,2222,2224,2226,2228,2230,2232,2234,2236,2238,2240,2242,2244,2246,2248,2250,2252,2254,2256,2258,2260,2262,2265,2267,2269,2271,2273,2275,2277,2279,2281,2283,2285,2287,2289,2291,2293,2295,2297,2299,2301,2303,2306,2308,2310,2312,2314,2316,2318,2320,2322,2324,2326,2328,2330,2332,2334,2336,2338,2340,2342,2344,2346,2348,2350,2352,2354,2356,2358,2360,2362,2364,2366,2368,2370,2372,2374,2376,2378,2380,2382,2384,2386,2388,2390,2392,2394,2396,2398,2400,2402,2404,2406,2408,2410,2412,2414,2416,2418,2420,2422,2424,2426,2428,2430,2432,2434,2436,2438,2440,2442,2444,2446,2448,2450,2452,2454,2456,2458,2460,2462,2464,2466,2468,2470,2472,2474,2476,2478,2480,2482,2484,2486,2488,2490,2492,2494,2496,2498,2500,2502,2504,2506,2508,2510,2512,2514,2516,2518,2520,2522,2524,2526,2528,2530,2532,2534,2536,2538,2540,2542,2544,2546,2548,2550,2552,2554,2556,2558,2560,2562,2564,2566,2568,2570,2572,2574,2576,2578,2580,2582,2584,2586,2588,2590,2592,2594,2596,2598,2600,2602,2604,2606,2608,2610,2612,2614,2616,2618,2620,2622,2624,2626,2628,2630,2632,2634,2636,2638,2640,2642,2644,2646,2648,2650,2652,2654,2656,2658,2660,2662,2664,2666,2668,2670,2672,2674,2676,2678,2680,2682,2684,2686,2688,2690,2692,2694,2696,2698,2700,2702,2704,2706,2708,2710,2712,2714,2716,2718,2720,2722,2724,2726,2728,2730,2732,2734,2736,2738,2740,2742,2744,2746,2748,2750,2752,2754,2756,2758,2760,2762,2764,2766,2768,2770,2772,2774,2776,2778,2780,2782,2784,2786,2788,2790,2792,2794,2796,2798,2800,2802,2804,2806,2808,2810,2812,2814,2816,2818,2820,2822,2824,2826,2828,2830,2832,2834,2836,2838,2840,2842,2844,2846,2848,2850,2852,2854,2856,2858,2860,2862,2864,2866,2868,2870,2872,2874,2876,2878,2880,2882,2884,2886,2888,2890,2892,2894,2896,2898,2900,2902,2904,2907,2909,2911,2913,2915,2917,2919,2921,2923,2925,2927,2929,2931,2933,2935,2937,2939,2941,2943,2945,2947,2949,2951,2953,2955,2957,2959,2961,2963,2965,2967,2969,2971,2973,2975,2977,2979,2981,2983,2985,2987,2989,2991,2993,2995,2997,2999,3001,3003,3005,3007,3009,3011,3013,3015,3017,3019,3022,3024,3026,3028,3030,3032,3034,3036,3038,3040,3042,3044,3046,3048,3050,3052,3054,3056,3058,3060,3062,3064,3066,3068,3070,3072,3074,3076,3078,3080,3082,3084,3086,3088,3090,3092,3094,3096,3098,3100,3102,3104,3106,3108,3110,3112,3114,3116,3118,3120,3122,3124,3126,3128,3130,3132,3134,3136,3138,3140,3142,3144,3146,3148,3150,3152,3154,3156,3158,3160,3162,3164,3166,3168,3170,3172,3174,3176,3178,3180,3182,3184,3186,3188,3190,3192,3194,3196,3198,3200,3202,3204,3206,3208,3210,3212,3214,3216,3218,3220,3222,3224,3226,3228,3230,3232,3234,3236,3238,3240,3242,3244,3246,3248,3250,3252,3254,3256,3258,3260,3262,3264,3266,3268,3270,3272,3274,3276,3278,3280,3282,3284,3286,3288,3290,3292,3294,3296,3298,3300,3302,3304,3306,3308,3310,3312,3314,3316,3318,3320,3322,3324,3326,3328,3330,3332,3334,3336,3338,3340,3342,3344,3346,3348,3350,3352,3354,3356,3358,3360,3362,3364,3366,3368,3370,3372,3374,3376,3378,3380,3382,3384,3386,3388,3390,3392,3394,3396,3398,3400,3402,3404,3406,3408,3410,3412,3414,3416,3418,3420,3422,3424,3426,3428,3430,3432,3434,3436,3438,3440,3442,3444,3446,3448,3450,3452,3454,3456,3458,3460,3462,3464,3466,3468,3470,3472,3474,3476,3478,3480,3482,3484,3486,3488,3490,3492,3494,3496,3498,3500,3502,3504,3506,3508,3510,3512,3514,3516,3518,3520,3522,3524,3526,3528,3530,3532,3534,3536,3538,3540,3542,3544,3546,3548,3550,3552,3554,3556,3558,3560,3562,3564,3566,3568,3570,3572,3574,3576,3578,3580,3582,3584,3586,3588,3590,3592,3594,3596,3598,3600,3602,3604,3606,3608,3610,3612,3614,3616,3618,3620,3622,3624,3626,3628,3630,3632,3634,3636,3638,3640,3642,3644,3646,3648,3650,3652,3654,3656,3658,3660,3662,3664,3666,3668,3670,3672,3674,3676,3678,3680,3682,3684,3686,3688,3690,3692,3694,3696,3698,3700,3702,3704,3706,3708,3710,3712,3714,3716,3718,3720,3722,3724,3726,3728,3730,3732,3734,3736,3738,3740,3742,3744,3746,3748,3750,3752,3754,3756,3758,3760,3762,3764,3766,3768,3770,3772,3774,3776,3778,3780,3782,3784,3786,3788,3790,3792,3794,3796,3798,3800,3802,3804,3806,3808,3810,3812,3814,3816,3818,3820,3822,3824,3826,3828,3830,3832,3834,3836,3838,3840,3842,3844,3846,3848,3850,3852,3854,3856,3858,3860,3862,3864,3866,3868,3870,3872,3874,3876,3878,3880,3882,3884,3886,3888,3890,3892,3894,3896,3898,3900,3902,3904,3906,3908,3910,3912,3914,3916,3918,3920,3922,3924,3926,3928,3930,3932,3934,3936,3938,3940,3942,3944,3946,3948,3950,3952,3954,3956,3958,3960,3962,3964,3966,3968,3970,3972,3974,3976,3978,3980,3982,3984,3986,3988,3990,3992,3994,3996,3998,4000,4002,4004,4006,4008,4010,4012,4014,4016,4018,4020,4022,4024,4026,4028,4030,4032,4034,4036,4038,4040,4042,4044,4046,4048,4050,4052,4054,4056,4058,4060,4062,4064,4066,4068,4070,4072,4074,4076,4078,4080,4082,4084,4086,4088,4090,4092,4094,4096,4098,4100,4102,4104,4106,4108,4110,4112,4114,4116,4118,4120,4122,4124,4126,4128,4130,4132,4134,4136,4138,4140,4142,4144,4146,4148,4150,4152,4154,4156,4158,4160,4162,4164,4166,4168,4170,4172,4174,4176,4178,4180,4182,4184,4186,4188,4190,4192,4194,4196,4198,4200,4202,4204,4206,4209,4211,4213,4215,4217,4219,4221,4223,4225,4227,4229,4231,4233,4235,4237,4239,4241,4243,4245,4247,4249,4251,4253,4255,4257,4259,4261,4263,4265,4267,4269,4271,4273,4275,4277,4279,4281,4283,4285,4287,4289,4291,4293,4295,4297,4299,4301,4303,4305,4307,4309,4311,4313,4315,4317,4319,4321,4323,4325,4327,4329,4331,4333,4335,4337,4339,4341,4343,4345,4347,4349,4351,4353,4355,4357,4359,4361,4363,4365,4367,4369,4371,4373,4375,4377,4379,4381,4383,4385,4387,4389,4391,4393,4395,4397,4399,4401,4403,4405,4407,4409,4411,4413,4415,4417,4419,4421,4423,4425,4427,4429,4431,4433,4435,4437,4439,4441,4443,4445,4447,4449,4451,4453,4455,4457,4459,4461,4463,4465,4467,4469,4471,4473,4475,4477,4479,4481,4483,4485,4487,4489,4491,4493,4495,4497,4499,4501,4503,4505,4507,4509,4511,4513,4515,4517,4519,4521,4523,4525,4527,4529,4531,4533,4535,4537,4539,4541,4543,4545,4547,4549,4551,4553,4555,4557,4559,4561,4563,4565,4567,4569,4571,4573,4575,4577,4579,4581,4583,4585,4587,4589,4591,4593,4595,4597,4599,4601,4603,4605,4607,4609,4611,4613,4615,4617,4619,4621,4623,4625,4627,4629,4631,4633,4635,4637,4639,4641,4643,4645,4647,4649,4651,4653,4655,4657,4659,4661,4663,4665,4667,4669,4671,4673,4675,4677,4679,4681,4683,4685,4687,4689,4691,4693,4695,4697,4699,4701,4703,4705,4707,4709,4711,4713,4715,4717,4719,4721,4723,4725,4727,4729,4731,4733,4735,4737,4739,4741,4743,4745,4747,4749,4751,4753,4755,4757,4759,4761,4763,4765,4767,4769,4771,4773,4775,4777,4779,4781,4783,4785,4787,4789,4791,4793,4795,4797,4799,4801,4803,4805,4807,4809,4811,4813,4815,4817,4819,4821,4823,4825,4827,4829,4831,4833,4835,4837,4839,4841,4843,4845,4847,4849,4851,4853,4855,4857,4859,4861,4863,4865,4867,4869,4871,4873,4875,4877,4879,4881,4883,4885,4887,4889,4891,4893,4895,4897,4899,4901,4903,4905,4907,4909,4911,4913,4915,4917,4919,4921,4923,4925,4927,4929,4931,4933,4935,4937,4939,4941,4943,4945,4947,4949,4951,4953,4955,4957,4959,4961,4963,4965,4967,4969,4971,4973,4975,4977,4979,4981,4983,4985,4987,4989,4991,4993,4995,4997,4999,5001,5003,5006,5008,5010,5012,5014,5016,5018,5020,5022,5024,5026,5028,5030,5032,5034,5036,5038,5040,5042,5044,5046,5048,5050,5052,5054,5056,5058,5060,5062,5064,5066,5068,5070,5072,5074,5076,5078,5080,5082,5084,5086,5088,5090,5092,5094,5096,5098,5100,5102,5104,5106,5108,5110,5112,5114,5116,5118,5120,5122,5124,5126,5128,5130,5132,5134,5136,5138,5140,5142,5144,5146,5148,5150,5152,5154,5156,5158,5160,5162,5164,5166,5168,5170,5172,5174,5176,5178,5180,5182,5184,5186,5188,5190,5192,5194,5197,5199,5201,5203,5205,5207,5209,5211,5213,5215,5217,5219,5221,5223,5225,5227,5229,5231,5233,5235,5237,5239,5241,5243,5245,5247,5249,5251,5253,5255,5257,5259,5261,5263,5265,5267,5269,5271,5273,5275,5277,5279,5281,5283,5285,5287,5289,5291,5293,5295,5297,5299,5301,5303,5305,5307,5309,5311,5313,5315,5317,5319,5321,5323,5325,5327,5329,5331,5333,5335,5337,5339,5341,5343,5345,5347,5349,5351,5353,5355,5357,5359,5361,5363,5365,5367,5369,5371,5373,5375,5377,5379,5381,5383,5385,5387,5389,5391,5393,5395,5397,5399,5401,5403,5405,5407,5409,5411,5413,5415,5417,5419,5421,5423,5425,5427,5429,5431,5433,5435,5437,5439,5441,5443,5445,5447,5449,5451,5453,5455,5457,5459,5461,5463,5465,5467,5469,5471,5473,5475,5477,5479,5481,5483,5485,5487,5489,5491,5493,5495,5497,5499,5501,5503,5505,5507,5509,5511,5513,5515,5517,5519,5521,5523,5525,5527,5529,5531,5533,5535,5537,5539,5541,5543,5545,5547,5549,5551,5553,5555,5557,5559,5561,5563,5565,5567,5569,5571,5573,5575,5577,5579,5581,5583,5585,5587,5589,5591,5593,5595,5597,5599,5601,5603,5605,5607,5609,5611,5613,5615,5617,5619,5621,5623,5625,5627,5629,5631,5633,5635,5637,5639,5641,5643,5645,5647,5649,5651,5653,5655,5657,5659,5661,5663,5665,5667,5669,5671,5673,5675,5677,5679,5681,5683,5685,5687,5689,5691,5693,5695,5697,5699,5701,5703,5705,5707,5709,5711,5713,5715,5717,5719,5721,5723,5725,5727,5729,5731,5733,5735,5737,5739,5741,5743,5745,5747,5749,5751,5753,5755,5757,5759,5761,5763,5765,5767,5769,5771,5773,5775,5777,5779,5781,5783,5785,5787,5789,5791,5793,5795,5797,5799,5801,5803,5805,5807,5809,5811,5813,5815,5817,5819,5821,5823,5825,5827,5829,5831,5833,5835,5837,5839,5841,5843,5845,5847,5849,5851,5853,5855,5857,5859,5861,5863,5865,5867,5869,5871,5873,5875,5877,5879,5881,5883,5885,5887,5889,5891,5893,5895,5897,5899,5901,5903,5905,5907,5909,5911,5913,5915,5917,5919,5921,5923,5925,5927,5929,5931,5933,5935,5937,5939,5941,5943,5945,5947,5949,5951,5953,5955,5957,5959,5961,5963,5965,5967,5969,5971,5973,5975,5977,5979,5981,5983,5985,5987,5989,5991,5993,5995,5997,5999,6001,6003,6005,6007,6009,6011,6013,6015,6017,6019,6021,6023,6025,6027,6029,6031,6033,6035,6037,6039,6041,6043,6045,6047,6049,6051,6053,6055,6057,6059,6061,6063,6065,6067,6069,6071,6073,6075,6077,6079,6081,6083,6085,6087,6089,6091,6093,6095,6097,6099,6101,6103,6105,6107,6109,6111,6113,6115,6117,6119,6121,6123,6125,6127,6129,6131,6133,6135,6137,6139,6141,6143,6145,6147,6149,6151,6153,6155,6157,6159,6161,6163,6165,6167,6169,6171,6173,6175,6177,6179,6181,6183,6185,6187,6189,6191,6193,6195,6197,6199,6201,6203,6205,6207,6209,6211,6213,6215,6217,6219,6221,6223,6225,6227,6229,6231,6233,6235,6237,6239,6241,6243,6245,6247,6249,6251,6253,6255,6257,6259,6261,6263,6265,6267,6269,6271,6273,6275,6277,6279,6281,6283,6285,6287,6289,6291,6293,6295,6297,6299,6301,6303,6305,6307,6309,6311,6313,6315,6317,6319,6321,6323,6325,6327,6329,6331,6333,6335,6337,6339,6341,6343,6345,6347,6349,6351,6353,6355,6357,6359,6361,6363,6365,6367,6369,6371,6373,6375,6377,6379,6381,6383,6385,6387,6389,6391,6393,6395,6397,6399,6401,6403,6405,6407,6409,6411,6413,6415,6417,6419,6421,6423,6425,6427,6429,6431,6433,6435,6437,6439,6441,6443,6445,6447,6449,6451,6453,6455,6457,6459,6461,6463,6465,6467,6469,6471,6473,6475,6477,6479,6481,6483,6485,6487,6489,6491,6493,6495],{"categories":81},[82],"AI & LLMs",{"categories":84},[85],"Developer Productivity",{"categories":87},[82],{"categories":89},[90],"Business & SaaS",{"categories":92},[82],{"categories":94},[95],"AI Automation",{"categories":97},[98],"Product Strategy",{"categories":100},[82],{"categories":102},[85],{"categories":104},[95],{"categories":106},[107],"Software Engineering",{"categories":109},[82],{"categories":111},[90],{"categories":113},[],{"categories":115},[82],{"categories":117},[118],"Inference & Serving",{"categories":120},[82],{"categories":122},[82],{"categories":124},[95],{"categories":126},[],{"categories":128},[129],"AI News & Trends",{"categories":131},[47],{"categories":133},[95],{"categories":135},[82],{"categories":137},[82],{"categories":139},[90],{"categories":141},[85],{"categories":143},[82],{"categories":145},[95],{"categories":147},[129],{"categories":149},[95],{"categories":151},[95],{"categories":153},[82],{"categories":155},[95],{"categories":157},[82],{"categories":159},[82],{"categories":161},[82],{"categories":163},[129],{"categories":165},[82],{"categories":167},[82],{"categories":169},[82],{"categories":171},[],{"categories":173},[174],"Design & Frontend",{"categories":176},[47],{"categories":178},[129],{"categories":180},[82],{"categories":182},[82],{"categories":184},[82],{"categories":186},[],{"categories":188},[82],{"categories":190},[82],{"categories":192},[95],{"categories":194},[107],{"categories":196},[82],{"categories":198},[95],{"categories":200},[82],{"categories":202},[203],"Marketing & Growth",{"categories":205},[174],{"categories":207},[82],{"categories":209},[95],{"categories":211},[82],{"categories":213},[107],{"categories":215},[],{"categories":217},[],{"categories":219},[174],{"categories":221},[82],{"categories":223},[95],{"categories":225},[85],{"categories":227},[107],{"categories":229},[95],{"categories":231},[174],{"categories":233},[98],{"categories":235},[82],{"categories":237},[107],{"categories":239},[240],"DevOps & Cloud",{"categories":242},[95],{"categories":244},[98],{"categories":246},[129],{"categories":248},[82],{"categories":250},[],{"categories":252},[82],{"categories":254},[82],{"categories":256},[],{"categories":258},[95],{"categories":260},[107],{"categories":262},[],{"categories":264},[107],{"categories":266},[82],{"categories":268},[269],"Governance & Standards",{"categories":271},[90],{"categories":273},[],{"categories":275},[],{"categories":277},[82],{"categories":279},[82],{"categories":281},[95],{"categories":283},[82],{"categories":285},[82],{"categories":287},[95],{"categories":289},[82],{"categories":291},[82],{"categories":293},[82],{"categories":295},[],{"categories":297},[107],{"categories":299},[],{"categories":301},[],{"categories":303},[82],{"categories":305},[107],{"categories":307},[],{"categories":309},[107],{"categories":311},[82],{"categories":313},[82],{"categories":315},[203],{"categories":317},[82],{"categories":319},[82],{"categories":321},[174],{"categories":323},[174],{"categories":325},[82],{"categories":327},[107],{"categories":329},[95],{"categories":331},[332],"GovTech & Public-Sector Adoption",{"categories":334},[107],{"categories":336},[82],{"categories":338},[82],{"categories":340},[82],{"categories":342},[95],{"categories":344},[95],{"categories":346},[47],{"categories":348},[82],{"categories":350},[129],{"categories":352},[95],{"categories":354},[355],"Legal AI Tools",{"categories":357},[82],{"categories":359},[95],{"categories":361},[82],{"categories":363},[203],{"categories":365},[95],{"categories":367},[98],{"categories":369},[82],{"categories":371},[107],{"categories":373},[332],{"categories":375},[],{"categories":377},[95],{"categories":379},[],{"categories":381},[90],{"categories":383},[95],{"categories":385},[95],{"categories":387},[388],"RAG & Retrieval",{"categories":390},[90],{"categories":392},[82],{"categories":394},[107],{"categories":396},[107],{"categories":398},[240],{"categories":400},[174],{"categories":402},[95],{"categories":404},[82],{"categories":406},[82],{"categories":408},[],{"categories":410},[411],"Agents & Orchestration",{"categories":413},[107],{"categories":415},[82],{"categories":417},[],{"categories":419},[95],{"categories":421},[90],{"categories":423},[],{"categories":425},[82],{"categories":427},[],{"categories":429},[82],{"categories":431},[85],{"categories":433},[107],{"categories":435},[90],{"categories":437},[82],{"categories":439},[95],{"categories":441},[82],{"categories":443},[129],{"categories":445},[82],{"categories":447},[],{"categories":449},[82],{"categories":451},[],{"categories":453},[107],{"categories":455},[82],{"categories":457},[47],{"categories":459},[],{"categories":461},[82],{"categories":463},[174],{"categories":465},[466],"Models & Frontier Labs",{"categories":468},[],{"categories":470},[174],{"categories":472},[473],"Regulation & Governance of AI",{"categories":475},[95],{"categories":477},[],{"categories":479},[82],{"categories":481},[82],{"categories":483},[95],{"categories":485},[129],{"categories":487},[90],{"categories":489},[82],{"categories":491},[],{"categories":493},[107],{"categories":495},[95],{"categories":497},[82],{"categories":499},[98],{"categories":501},[502],"AI Policy & Regulation",{"categories":504},[],{"categories":506},[82],{"categories":508},[95],{"categories":510},[98],{"categories":512},[95],{"categories":514},[82],{"categories":516},[82],{"categories":518},[82],{"categories":520},[95],{"categories":522},[],{"categories":524},[47],{"categories":526},[527],"Evals & Reliability",{"categories":529},[82],{"categories":531},[82],{"categories":533},[],{"categories":535},[85],{"categories":537},[332],{"categories":539},[502],{"categories":541},[82],{"categories":543},[90],{"categories":545},[82],{"categories":547},[95],{"categories":549},[82],{"categories":551},[95],{"categories":553},[411],{"categories":555},[82],{"categories":557},[107],{"categories":559},[82],{"categories":561},[],{"categories":563},[],{"categories":565},[82],{"categories":567},[332],{"categories":569},[82],{"categories":571},[82],{"categories":573},[82],{"categories":575},[],{"categories":577},[174],{"categories":579},[],{"categories":581},[82],{"categories":583},[],{"categories":585},[95],{"categories":587},[82],{"categories":589},[174],{"categories":591},[],{"categories":593},[82],{"categories":595},[82],{"categories":597},[47],{"categories":599},[95],{"categories":601},[82],{"categories":603},[90],{"categories":605},[95],{"categories":607},[82],{"categories":609},[82],{"categories":611},[107],{"categories":613},[174],{"categories":615},[82],{"categories":617},[95],{"categories":619},[],{"categories":621},[107],{"categories":623},[95],{"categories":625},[47],{"categories":627},[],{"categories":629},[82],{"categories":631},[129],{"categories":633},[82],{"categories":635},[],{"categories":637},[82],{"categories":639},[82],{"categories":641},[82],{"categories":643},[90,203],{"categories":645},[],{"categories":647},[82],{"categories":649},[82],{"categories":651},[95],{"categories":653},[82],{"categories":655},[],{"categories":657},[],{"categories":659},[82],{"categories":661},[174],{"categories":663},[82],{"categories":665},[],{"categories":667},[82],{"categories":669},[240],{"categories":671},[],{"categories":673},[95],{"categories":675},[129],{"categories":677},[82],{"categories":679},[82],{"categories":681},[174],{"categories":683},[],{"categories":685},[129],{"categories":687},[82],{"categories":689},[118],{"categories":691},[82],{"categories":693},[82],{"categories":695},[95],{"categories":697},[129],{"categories":699},[466],{"categories":701},[82],{"categories":703},[203],{"categories":705},[],{"categories":707},[95],{"categories":709},[90],{"categories":711},[107],{"categories":713},[82],{"categories":715},[95],{"categories":717},[],{"categories":719},[82,240],{"categories":721},[82],{"categories":723},[82],{"categories":725},[82],{"categories":727},[95],{"categories":729},[82,107],{"categories":731},[47],{"categories":733},[82],{"categories":735},[82],{"categories":737},[107],{"categories":739},[82],{"categories":741},[95],{"categories":743},[502],{"categories":745},[203],{"categories":747},[82],{"categories":749},[95],{"categories":751},[82],{"categories":753},[82],{"categories":755},[95],{"categories":757},[],{"categories":759},[95],{"categories":761},[82],{"categories":763},[82],{"categories":765},[95],{"categories":767},[82],{"categories":769},[82,90],{"categories":771},[82],{"categories":773},[90],{"categories":775},[],{"categories":777},[174],{"categories":779},[174],{"categories":781},[82],{"categories":783},[],{"categories":785},[],{"categories":787},[82],{"categories":789},[129],{"categories":791},[],{"categories":793},[85],{"categories":795},[82],{"categories":797},[107],{"categories":799},[82],{"categories":801},[802],"Generative UI & Design-to-Code",{"categories":804},[82],{"categories":806},[82],{"categories":808},[174],{"categories":810},[82],{"categories":812},[813],"Algorithmic Accountability",{"categories":815},[95],{"categories":817},[107],{"categories":819},[129],{"categories":821},[174],{"categories":823},[82],{"categories":825},[],{"categories":827},[98],{"categories":829},[82],{"categories":831},[82],{"categories":833},[82],{"categories":835},[95],{"categories":837},[838],"MLOps & Infrastructure",{"categories":840},[82],{"categories":842},[82],{"categories":844},[82],{"categories":846},[82],{"categories":848},[82],{"categories":850},[129],{"categories":852},[98],{"categories":854},[85],{"categories":856},[82],{"categories":858},[95],{"categories":860},[240],{"categories":862},[82],{"categories":864},[90],{"categories":866},[82],{"categories":868},[174],{"categories":870},[82],{"categories":872},[82],{"categories":874},[95],{"categories":876},[],{"categories":878},[],{"categories":880},[82],{"categories":882},[118],{"categories":884},[174],{"categories":886},[129],{"categories":888},[47],{"categories":890},[],{"categories":892},[82],{"categories":894},[82],{"categories":896},[90],{"categories":898},[95],{"categories":900},[82],{"categories":902},[82],{"categories":904},[82],{"categories":906},[82],{"categories":908},[129],{"categories":910},[118],{"categories":912},[82],{"categories":914},[174],{"categories":916},[82],{"categories":918},[],{"categories":920},[95],{"categories":922},[107],{"categories":924},[],{"categories":926},[82],{"categories":928},[82],{"categories":930},[95],{"categories":932},[107],{"categories":934},[82],{"categories":936},[47],{"categories":938},[],{"categories":940},[82],{"categories":942},[],{"categories":944},[82],{"categories":946},[],{"categories":948},[98],{"categories":950},[90],{"categories":952},[95],{"categories":954},[95],{"categories":956},[],{"categories":958},[85],{"categories":960},[82],{"categories":962},[82],{"categories":964},[90],{"categories":966},[129],{"categories":968},[85],{"categories":970},[],{"categories":972},[82],{"categories":974},[],{"categories":976},[],{"categories":978},[129],{"categories":980},[129],{"categories":982},[],{"categories":984},[411],{"categories":986},[82],{"categories":988},[174],{"categories":990},[107],{"categories":992},[],{"categories":994},[355],{"categories":996},[95],{"categories":998},[90],{"categories":1000},[],{"categories":1002},[],{"categories":1004},[85],{"categories":1006},[47],{"categories":1008},[],{"categories":1010},[203],{"categories":1012},[95],{"categories":1014},[90],{"categories":1016},[95],{"categories":1018},[90],{"categories":1020},[82],{"categories":1022},[107],{"categories":1024},[],{"categories":1026},[118],{"categories":1028},[98],{"categories":1030},[82],{"categories":1032},[174],{"categories":1034},[107],{"categories":1036},[90],{"categories":1038},[82],{"categories":1040},[95],{"categories":1042},[90],{"categories":1044},[82],{"categories":1046},[82],{"categories":1048},[82],{"categories":1050},[82],{"categories":1052},[82],{"categories":1054},[],{"categories":1056},[],{"categories":1058},[107],{"categories":1060},[47],{"categories":1062},[98],{"categories":1064},[82],{"categories":1066},[95],{"categories":1068},[107],{"categories":1070},[82],{"categories":1072},[],{"categories":1074},[129],{"categories":1076},[98],{"categories":1078},[107],{"categories":1080},[82],{"categories":1082},[527],{"categories":1084},[240],{"categories":1086},[],{"categories":1088},[95],{"categories":1090},[82],{"categories":1092},[],{"categories":1094},[85],{"categories":1096},[],{"categories":1098},[82],{"categories":1100},[82],{"categories":1102},[82],{"categories":1104},[174],{"categories":1106},[203],{"categories":1108},[82],{"categories":1110},[107],{"categories":1112},[82],{"categories":1114},[95],{"categories":1116},[],{"categories":1118},[107],{"categories":1120},[82],{"categories":1122},[85],{"categories":1124},[],{"categories":1126},[90],{"categories":1128},[82],{"categories":1130},[129],{"categories":1132},[82,240],{"categories":1134},[82],{"categories":1136},[1137],"Design Systems for AI",{"categories":1139},[82],{"categories":1141},[82],{"categories":1143},[129],{"categories":1145},[82],{"categories":1147},[82],{"categories":1149},[82],{"categories":1151},[90],{"categories":1153},[82],{"categories":1155},[82],{"categories":1157},[82],{"categories":1159},[],{"categories":1161},[82],{"categories":1163},[82],{"categories":1165},[90],{"categories":1167},[82],{"categories":1169},[],{"categories":1171},[95],{"categories":1173},[107],{"categories":1175},[129],{"categories":1177},[107],{"categories":1179},[82],{"categories":1181},[174],{"categories":1183},[129],{"categories":1185},[47],{"categories":1187},[82],{"categories":1189},[82],{"categories":1191},[95],{"categories":1193},[85],{"categories":1195},[502],{"categories":1197},[82],{"categories":1199},[95],{"categories":1201},[82],{"categories":1203},[107],{"categories":1205},[107],{"categories":1207},[],{"categories":1209},[],{"categories":1211},[95],{"categories":1213},[98],{"categories":1215},[],{"categories":1217},[90],{"categories":1219},[82],{"categories":1221},[],{"categories":1223},[174],{"categories":1225},[95],{"categories":1227},[107],{"categories":1229},[174],{"categories":1231},[82],{"categories":1233},[82],{"categories":1235},[174],{"categories":1237},[],{"categories":1239},[],{"categories":1241},[129],{"categories":1243},[95],{"categories":1245},[95],{"categories":1247},[82],{"categories":1249},[82],{"categories":1251},[82],{"categories":1253},[82],{"categories":1255},[90],{"categories":1257},[82],{"categories":1259},[82],{"categories":1261},[],{"categories":1263},[107],{"categories":1265},[107],{"categories":1267},[82],{"categories":1269},[107],{"categories":1271},[90],{"categories":1273},[],{"categories":1275},[82],{"categories":1277},[82],{"categories":1279},[82],{"categories":1281},[82],{"categories":1283},[82],{"categories":1285},[95],{"categories":1287},[85],{"categories":1289},[90],{"categories":1291},[82],{"categories":1293},[95],{"categories":1295},[129],{"categories":1297},[95],{"categories":1299},[118],{"categories":1301},[203],{"categories":1303},[82],{"categories":1305},[95],{"categories":1307},[82],{"categories":1309},[82],{"categories":1311},[],{"categories":1313},[174],{"categories":1315},[],{"categories":1317},[82],{"categories":1319},[82],{"categories":1321},[],{"categories":1323},[107],{"categories":1325},[90],{"categories":1327},[1328],"Visual & Generative Media",{"categories":1330},[95],{"categories":1332},[],{"categories":1334},[82],{"categories":1336},[82],{"categories":1338},[107],{"categories":1340},[240],{"categories":1342},[47],{"categories":1344},[502],{"categories":1346},[107],{"categories":1348},[203],{"categories":1350},[82],{"categories":1352},[174],{"categories":1354},[82],{"categories":1356},[82],{"categories":1358},[107],{"categories":1360},[95],{"categories":1362},[82],{"categories":1364},[],{"categories":1366},[],{"categories":1368},[95],{"categories":1370},[107],{"categories":1372},[85],{"categories":1374},[95],{"categories":1376},[466],{"categories":1378},[82],{"categories":1380},[98],{"categories":1382},[82],{"categories":1384},[90],{"categories":1386},[],{"categories":1388},[82],{"categories":1390},[98],{"categories":1392},[82],{"categories":1394},[82],{"categories":1396},[82],{"categories":1398},[98],{"categories":1400},[82],{"categories":1402},[82],{"categories":1404},[203],{"categories":1406},[82],{"categories":1408},[411],{"categories":1410},[82],{"categories":1412},[95],{"categories":1414},[82],{"categories":1416},[82],{"categories":1418},[82],{"categories":1420},[82],{"categories":1422},[174],{"categories":1424},[95],{"categories":1426},[],{"categories":1428},[95],{"categories":1430},[],{"categories":1432},[240],{"categories":1434},[107],{"categories":1436},[],{"categories":1438},[466],{"categories":1440},[82],{"categories":1442},[95],{"categories":1444},[82],{"categories":1446},[174,82],{"categories":1448},[85],{"categories":1450},[82],{"categories":1452},[174],{"categories":1454},[],{"categories":1456},[82],{"categories":1458},[85],{"categories":1460},[1461],"Medical Imaging & Radiology",{"categories":1463},[82],{"categories":1465},[174],{"categories":1467},[95],{"categories":1469},[107],{"categories":1471},[],{"categories":1473},[82],{"categories":1475},[82],{"categories":1477},[82],{"categories":1479},[],{"categories":1481},[],{"categories":1483},[82],{"categories":1485},[411],{"categories":1487},[82],{"categories":1489},[85],{"categories":1491},[82],{"categories":1493},[82],{"categories":1495},[],{"categories":1497},[95],{"categories":1499},[82],{"categories":1501},[98],{"categories":1503},[107],{"categories":1505},[82],{"categories":1507},[411],{"categories":1509},[82],{"categories":1511},[95],{"categories":1513},[82],{"categories":1515},[82],{"categories":1517},[82],{"categories":1519},[174],{"categories":1521},[95],{"categories":1523},[240],{"categories":1525},[174],{"categories":1527},[90],{"categories":1529},[95],{"categories":1531},[129],{"categories":1533},[82],{"categories":1535},[82],{"categories":1537},[98],{"categories":1539},[82],{"categories":1541},[82],{"categories":1543},[82],{"categories":1545},[95],{"categories":1547},[107],{"categories":1549},[107],{"categories":1551},[82],{"categories":1553},[98],{"categories":1555},[],{"categories":1557},[129],{"categories":1559},[],{"categories":1561},[98],{"categories":1563},[95],{"categories":1565},[82],{"categories":1567},[95],{"categories":1569},[1137],{"categories":1571},[1137],{"categories":1573},[174],{"categories":1575},[82],{"categories":1577},[82],{"categories":1579},[95],{"categories":1581},[107],{"categories":1583},[174],{"categories":1585},[95],{"categories":1587},[129],{"categories":1589},[],{"categories":1591},[82],{"categories":1593},[],{"categories":1595},[82],{"categories":1597},[82],{"categories":1599},[82],{"categories":1601},[82],{"categories":1603},[95],{"categories":1605},[1606],"Contract Review & E-Discovery",{"categories":1608},[82],{"categories":1610},[174],{"categories":1612},[82],{"categories":1614},[85],{"categories":1616},[82],{"categories":1618},[129],{"categories":1620},[82],{"categories":1622},[82],{"categories":1624},[203],{"categories":1626},[107],{"categories":1628},[82],{"categories":1630},[82],{"categories":1632},[95],{"categories":1634},[95],{"categories":1636},[813],{"categories":1638},[82],{"categories":1640},[82],{"categories":1642},[95],{"categories":1644},[95],{"categories":1646},[82],{"categories":1648},[82],{"categories":1650},[95],{"categories":1652},[82],{"categories":1654},[82],{"categories":1656},[411],{"categories":1658},[388],{"categories":1660},[82],{"categories":1662},[95],{"categories":1664},[82],{"categories":1666},[1667],"Law-Firm Practice & Adoption",{"categories":1669},[82],{"categories":1671},[95],{"categories":1673},[174],{"categories":1675},[82],{"categories":1677},[82],{"categories":1679},[82],{"categories":1681},[],{"categories":1683},[],{"categories":1685},[107],{"categories":1687},[82],{"categories":1689},[],{"categories":1691},[95],{"categories":1693},[85],{"categories":1695},[240],{"categories":1697},[82],{"categories":1699},[],{"categories":1701},[85],{"categories":1703},[90],{"categories":1705},[82],{"categories":1707},[203],{"categories":1709},[],{"categories":1711},[90],{"categories":1713},[90],{"categories":1715},[],{"categories":1717},[82],{"categories":1719},[98],{"categories":1721},[82],{"categories":1723},[107],{"categories":1725},[],{"categories":1727},[],{"categories":1729},[],{"categories":1731},[],{"categories":1733},[82],{"categories":1735},[95],{"categories":1737},[240],{"categories":1739},[82],{"categories":1741},[85],{"categories":1743},[107],{"categories":1745},[82],{"categories":1747},[82],{"categories":1749},[107],{"categories":1751},[98],{"categories":1753},[82],{"categories":1755},[82],{"categories":1757},[82],{"categories":1759},[838],{"categories":1761},[82],{"categories":1763},[82],{"categories":1765},[203],{"categories":1767},[107],{"categories":1769},[90],{"categories":1771},[82],{"categories":1773},[82],{"categories":1775},[174],{"categories":1777},[82],{"categories":1779},[82],{"categories":1781},[82],{"categories":1783},[82],{"categories":1785},[95],{"categories":1787},[82,85],{"categories":1789},[411],{"categories":1791},[82],{"categories":1793},[82],{"categories":1795},[107],{"categories":1797},[107],{"categories":1799},[174],{"categories":1801},[95],{"categories":1803},[107],{"categories":1805},[82],{"categories":1807},[82],{"categories":1809},[],{"categories":1811},[],{"categories":1813},[82],{"categories":1815},[95],{"categories":1817},[],{"categories":1819},[82],{"categories":1821},[107],{"categories":1823},[47],{"categories":1825},[129],{"categories":1827},[174],{"categories":1829},[82],{"categories":1831},[82],{"categories":1833},[107],{"categories":1835},[],{"categories":1837},[95],{"categories":1839},[82],{"categories":1841},[82],{"categories":1843},[82],{"categories":1845},[82],{"categories":1847},[],{"categories":1849},[95],{"categories":1851},[82],{"categories":1853},[82],{"categories":1855},[],{"categories":1857},[95],{"categories":1859},[82],{"categories":1861},[82],{"categories":1863},[90],{"categories":1865},[82],{"categories":1867},[82],{"categories":1869},[],{"categories":1871},[85],{"categories":1873},[82],{"categories":1875},[82],{"categories":1877},[174],{"categories":1879},[107],{"categories":1881},[82],{"categories":1883},[85],{"categories":1885},[82],{"categories":1887},[107],{"categories":1889},[203],{"categories":1891},[95],{"categories":1893},[95],{"categories":1895},[82],{"categories":1897},[82],{"categories":1899},[82,174],{"categories":1901},[82],{"categories":1903},[95],{"categories":1905},[129],{"categories":1907},[82],{"categories":1909},[129],{"categories":1911},[95],{"categories":1913},[174],{"categories":1915},[82],{"categories":1917},[],{"categories":1919},[107],{"categories":1921},[240],{"categories":1923},[174],{"categories":1925},[107],{"categories":1927},[82],{"categories":1929},[98],{"categories":1931},[82],{"categories":1933},[82],{"categories":1935},[95],{"categories":1937},[],{"categories":1939},[],{"categories":1941},[82],{"categories":1943},[],{"categories":1945},[],{"categories":1947},[98],{"categories":1949},[107],{"categories":1951},[82],{"categories":1953},[95],{"categories":1955},[95],{"categories":1957},[90],{"categories":1959},[95],{"categories":1961},[240],{"categories":1963},[82],{"categories":1965},[82],{"categories":1967},[82],{"categories":1969},[118],{"categories":1971},[82],{"categories":1973},[82],{"categories":1975},[107],{"categories":1977},[95],{"categories":1979},[82],{"categories":1981},[82],{"categories":1983},[355],{"categories":1985},[813],{"categories":1987},[],{"categories":1989},[174],{"categories":1991},[1667],{"categories":1993},[107],{"categories":1995},[],{"categories":1997},[],{"categories":1999},[95],{"categories":2001},[],{"categories":2003},[],{"categories":2005},[82],{"categories":2007},[203],{"categories":2009},[82],{"categories":2011},[203],{"categories":2013},[95],{"categories":2015},[82],{"categories":2017},[107],{"categories":2019},[98],{"categories":2021},[],{"categories":2023},[82],{"categories":2025},[82],{"categories":2027},[107],{"categories":2029},[1606],{"categories":2031},[174],{"categories":2033},[174],{"categories":2035},[82],{"categories":2037},[95],{"categories":2039},[85],{"categories":2041},[82],{"categories":2043},[82],{"categories":2045},[82],{"categories":2047},[174],{"categories":2049},[174],{"categories":2051},[95],{"categories":2053},[95],{"categories":2055},[95],{"categories":2057},[82],{"categories":2059},[82],{"categories":2061},[],{"categories":2063},[82],{"categories":2065},[],{"categories":2067},[2068],"Interaction & Product Design",{"categories":2070},[82],{"categories":2072},[95],{"categories":2074},[107],{"categories":2076},[269],{"categories":2078},[129],{"categories":2080},[107],{"categories":2082},[82],{"categories":2084},[82],{"categories":2086},[107],{"categories":2088},[85],{"categories":2090},[95],{"categories":2092},[82],{"categories":2094},[],{"categories":2096},[95],{"categories":2098},[95],{"categories":2100},[],{"categories":2102},[107],{"categories":2104},[82],{"categories":2106},[85],{"categories":2108},[2068],{"categories":2110},[82],{"categories":2112},[85],{"categories":2114},[85],{"categories":2116},[],{"categories":2118},[95],{"categories":2120},[107],{"categories":2122},[],{"categories":2124},[95],{"categories":2126},[129],{"categories":2128},[82],{"categories":2130},[95],{"categories":2132},[82],{"categories":2134},[95],{"categories":2136},[82],{"categories":2138},[82],{"categories":2140},[129],{"categories":2142},[47],{"categories":2144},[82],{"categories":2146},[98],{"categories":2148},[107],{"categories":2150},[2151],"Coding Agents & Dev Productivity",{"categories":2153},[129],{"categories":2155},[174],{"categories":2157},[82],{"categories":2159},[82],{"categories":2161},[],{"categories":2163},[82],{"categories":2165},[813],{"categories":2167},[],{"categories":2169},[82],{"categories":2171},[240],{"categories":2173},[82],{"categories":2175},[129],{"categories":2177},[],{"categories":2179},[],{"categories":2181},[82],{"categories":2183},[],{"categories":2185},[95],{"categories":2187},[82],{"categories":2189},[],{"categories":2191},[107],{"categories":2193},[107],{"categories":2195},[82],{"categories":2197},[47],{"categories":2199},[],{"categories":2201},[82],{"categories":2203},[82],{"categories":2205},[82],{"categories":2207},[47],{"categories":2209},[107],{"categories":2211},[95],{"categories":2213},[],{"categories":2215},[],{"categories":2217},[82],{"categories":2219},[82],{"categories":2221},[95],{"categories":2223},[95],{"categories":2225},[332],{"categories":2227},[107],{"categories":2229},[107],{"categories":2231},[95],{"categories":2233},[129],{"categories":2235},[129],{"categories":2237},[95],{"categories":2239},[95],{"categories":2241},[82],{"categories":2243},[85],{"categories":2245},[2068],{"categories":2247},[82,240],{"categories":2249},[47],{"categories":2251},[],{"categories":2253},[174],{"categories":2255},[107],{"categories":2257},[85],{"categories":2259},[82],{"categories":2261},[95],{"categories":2263},[2264],"The Designer's Role & Craft",{"categories":2266},[174],{"categories":2268},[],{"categories":2270},[95],{"categories":2272},[82],{"categories":2274},[95],{"categories":2276},[95],{"categories":2278},[82],{"categories":2280},[203],{"categories":2282},[82],{"categories":2284},[107],{"categories":2286},[82],{"categories":2288},[174],{"categories":2290},[82],{"categories":2292},[],{"categories":2294},[95],{"categories":2296},[174],{"categories":2298},[82],{"categories":2300},[82],{"categories":2302},[82],{"categories":2304},[2305],"AI UX Patterns",{"categories":2307},[95],{"categories":2309},[95],{"categories":2311},[95],{"categories":2313},[95],{"categories":2315},[203],{"categories":2317},[47],{"categories":2319},[82],{"categories":2321},[95],{"categories":2323},[82],{"categories":2325},[1137],{"categories":2327},[],{"categories":2329},[203],{"categories":2331},[95],{"categories":2333},[129],{"categories":2335},[107],{"categories":2337},[82],{"categories":2339},[95],{"categories":2341},[],{"categories":2343},[],{"categories":2345},[82],{"categories":2347},[95],{"categories":2349},[82],{"categories":2351},[95],{"categories":2353},[332],{"categories":2355},[174],{"categories":2357},[82],{"categories":2359},[129],{"categories":2361},[107],{"categories":2363},[82],{"categories":2365},[95],{"categories":2367},[95],{"categories":2369},[],{"categories":2371},[82],{"categories":2373},[],{"categories":2375},[],{"categories":2377},[82],{"categories":2379},[82],{"categories":2381},[82],{"categories":2383},[95],{"categories":2385},[107],{"categories":2387},[],{"categories":2389},[],{"categories":2391},[47],{"categories":2393},[118],{"categories":2395},[82],{"categories":2397},[82],{"categories":2399},[47],{"categories":2401},[82],{"categories":2403},[129],{"categories":2405},[82],{"categories":2407},[82],{"categories":2409},[82],{"categories":2411},[95],{"categories":2413},[82],{"categories":2415},[95],{"categories":2417},[82],{"categories":2419},[82],{"categories":2421},[95],{"categories":2423},[],{"categories":2425},[],{"categories":2427},[82],{"categories":2429},[240],{"categories":2431},[82],{"categories":2433},[],{"categories":2435},[],{"categories":2437},[174],{"categories":2439},[838],{"categories":2441},[95],{"categories":2443},[85],{"categories":2445},[2264],{"categories":2447},[],{"categories":2449},[],{"categories":2451},[82],{"categories":2453},[],{"categories":2455},[],{"categories":2457},[107],{"categories":2459},[129],{"categories":2461},[203],{"categories":2463},[90],{"categories":2465},[82],{"categories":2467},[82],{"categories":2469},[90],{"categories":2471},[],{"categories":2473},[174],{"categories":2475},[98],{"categories":2477},[82],{"categories":2479},[82],{"categories":2481},[95],{"categories":2483},[90],{"categories":2485},[82],{"categories":2487},[82],{"categories":2489},[85],{"categories":2491},[82],{"categories":2493},[],{"categories":2495},[85],{"categories":2497},[82],{"categories":2499},[203],{"categories":2501},[95],{"categories":2503},[129],{"categories":2505},[82],{"categories":2507},[107],{"categories":2509},[82],{"categories":2511},[82],{"categories":2513},[90],{"categories":2515},[82],{"categories":2517},[82],{"categories":2519},[82],{"categories":2521},[95],{"categories":2523},[],{"categories":2525},[82],{"categories":2527},[107],{"categories":2529},[85],{"categories":2531},[82],{"categories":2533},[82],{"categories":2535},[82],{"categories":2537},[],{"categories":2539},[82],{"categories":2541},[411],{"categories":2543},[95],{"categories":2545},[90],{"categories":2547},[129],{"categories":2549},[82],{"categories":2551},[82],{"categories":2553},[],{"categories":2555},[90],{"categories":2557},[90],{"categories":2559},[82],{"categories":2561},[82],{"categories":2563},[98],{"categories":2565},[82],{"categories":2567},[82],{"categories":2569},[82],{"categories":2571},[82],{"categories":2573},[107],{"categories":2575},[107],{"categories":2577},[82],{"categories":2579},[],{"categories":2581},[107],{"categories":2583},[82],{"categories":2585},[107],{"categories":2587},[95],{"categories":2589},[502],{"categories":2591},[],{"categories":2593},[],{"categories":2595},[82],{"categories":2597},[129],{"categories":2599},[],{"categories":2601},[240],{"categories":2603},[82],{"categories":2605},[82],{"categories":2607},[174],{"categories":2609},[802],{"categories":2611},[],{"categories":2613},[82],{"categories":2615},[82],{"categories":2617},[82],{"categories":2619},[107],{"categories":2621},[82],{"categories":2623},[82],{"categories":2625},[82,240],{"categories":2627},[82],{"categories":2629},[82],{"categories":2631},[174],{"categories":2633},[95],{"categories":2635},[],{"categories":2637},[95],{"categories":2639},[95],{"categories":2641},[82],{"categories":2643},[82],{"categories":2645},[82],{"categories":2647},[82],{"categories":2649},[47],{"categories":2651},[82],{"categories":2653},[2305],{"categories":2655},[85],{"categories":2657},[47],{"categories":2659},[85],{"categories":2661},[107],{"categories":2663},[174],{"categories":2665},[95],{"categories":2667},[82],{"categories":2669},[],{"categories":2671},[90],{"categories":2673},[82],{"categories":2675},[82],{"categories":2677},[129],{"categories":2679},[82],{"categories":2681},[82],{"categories":2683},[95],{"categories":2685},[82],{"categories":2687},[82],{"categories":2689},[82],{"categories":2691},[90],{"categories":2693},[],{"categories":2695},[240],{"categories":2697},[82],{"categories":2699},[332],{"categories":2701},[174],{"categories":2703},[174],{"categories":2705},[107],{"categories":2707},[95],{"categories":2709},[82],{"categories":2711},[90],{"categories":2713},[129],{"categories":2715},[82],{"categories":2717},[82],{"categories":2719},[174],{"categories":2721},[95],{"categories":2723},[95],{"categories":2725},[82],{"categories":2727},[82],{"categories":2729},[466],{"categories":2731},[],{"categories":2733},[82],{"categories":2735},[82],{"categories":2737},[82],{"categories":2739},[],{"categories":2741},[],{"categories":2743},[82],{"categories":2745},[82],{"categories":2747},[95],{"categories":2749},[82],{"categories":2751},[82],{"categories":2753},[82],{"categories":2755},[107],{"categories":2757},[82],{"categories":2759},[82],{"categories":2761},[95],{"categories":2763},[82],{"categories":2765},[82],{"categories":2767},[82],{"categories":2769},[82],{"categories":2771},[82],{"categories":2773},[],{"categories":2775},[107],{"categories":2777},[47],{"categories":2779},[82],{"categories":2781},[95],{"categories":2783},[82],{"categories":2785},[],{"categories":2787},[],{"categories":2789},[82],{"categories":2791},[82],{"categories":2793},[82],{"categories":2795},[129],{"categories":2797},[47],{"categories":2799},[],{"categories":2801},[82],{"categories":2803},[174],{"categories":2805},[82],{"categories":2807},[240],{"categories":2809},[1667],{"categories":2811},[129],{"categories":2813},[107],{"categories":2815},[107],{"categories":2817},[107],{"categories":2819},[82],{"categories":2821},[82],{"categories":2823},[129],{"categories":2825},[129],{"categories":2827},[240],{"categories":2829},[95],{"categories":2831},[],{"categories":2833},[129],{"categories":2835},[82],{"categories":2837},[85],{"categories":2839},[107],{"categories":2841},[82],{"categories":2843},[129],{"categories":2845},[],{"categories":2847},[82],{"categories":2849},[107],{"categories":2851},[107],{"categories":2853},[47],{"categories":2855},[82],{"categories":2857},[129],{"categories":2859},[82],{"categories":2861},[107],{"categories":2863},[95],{"categories":2865},[129],{"categories":2867},[95],{"categories":2869},[240],{"categories":2871},[95],{"categories":2873},[82],{"categories":2875},[82],{"categories":2877},[82],{"categories":2879},[82],{"categories":2881},[107],{"categories":2883},[82],{"categories":2885},[],{"categories":2887},[95],{"categories":2889},[90],{"categories":2891},[107],{"categories":2893},[],{"categories":2895},[],{"categories":2897},[82],{"categories":2899},[95],{"categories":2901},[82],{"categories":2903},[82],{"categories":2905},[2906],"Frameworks & Tooling",{"categories":2908},[82],{"categories":2910},[82],{"categories":2912},[107],{"categories":2914},[82],{"categories":2916},[82],{"categories":2918},[],{"categories":2920},[47],{"categories":2922},[47],{"categories":2924},[85],{"categories":2926},[82],{"categories":2928},[95],{"categories":2930},[82],{"categories":2932},[174],{"categories":2934},[],{"categories":2936},[1667],{"categories":2938},[82],{"categories":2940},[107],{"categories":2942},[82],{"categories":2944},[240],{"categories":2946},[240],{"categories":2948},[],{"categories":2950},[95],{"categories":2952},[82],{"categories":2954},[129],{"categories":2956},[129],{"categories":2958},[82],{"categories":2960},[95],{"categories":2962},[],{"categories":2964},[174],{"categories":2966},[82],{"categories":2968},[82],{"categories":2970},[],{"categories":2972},[82],{"categories":2974},[95],{"categories":2976},[82],{"categories":2978},[82],{"categories":2980},[],{"categories":2982},[107],{"categories":2984},[82],{"categories":2986},[107],{"categories":2988},[240],{"categories":2990},[82],{"categories":2992},[82],{"categories":2994},[107],{"categories":2996},[90],{"categories":2998},[82],{"categories":3000},[1667],{"categories":3002},[],{"categories":3004},[95],{"categories":3006},[85],{"categories":3008},[82],{"categories":3010},[85],{"categories":3012},[82],{"categories":3014},[],{"categories":3016},[95],{"categories":3018},[82],{"categories":3020},[3021],"AI Design Tooling",{"categories":3023},[174],{"categories":3025},[82],{"categories":3027},[82],{"categories":3029},[107],{"categories":3031},[174],{"categories":3033},[82],{"categories":3035},[107],{"categories":3037},[129],{"categories":3039},[98],{"categories":3041},[107],{"categories":3043},[82],{"categories":3045},[82],{"categories":3047},[95],{"categories":3049},[82],{"categories":3051},[],{"categories":3053},[82],{"categories":3055},[82],{"categories":3057},[95],{"categories":3059},[82],{"categories":3061},[82],{"categories":3063},[82],{"categories":3065},[95],{"categories":3067},[],{"categories":3069},[95],{"categories":3071},[2906],{"categories":3073},[82],{"categories":3075},[82],{"categories":3077},[95],{"categories":3079},[95],{"categories":3081},[107],{"categories":3083},[107],{"categories":3085},[],{"categories":3087},[107],{"categories":3089},[82],{"categories":3091},[82],{"categories":3093},[95],{"categories":3095},[90],{"categories":3097},[82],{"categories":3099},[],{"categories":3101},[82],{"categories":3103},[82],{"categories":3105},[2068],{"categories":3107},[],{"categories":3109},[82],{"categories":3111},[82],{"categories":3113},[82],{"categories":3115},[82],{"categories":3117},[174],{"categories":3119},[82],{"categories":3121},[],{"categories":3123},[82],{"categories":3125},[82],{"categories":3127},[82],{"categories":3129},[203],{"categories":3131},[129],{"categories":3133},[82],{"categories":3135},[82],{"categories":3137},[1667],{"categories":3139},[85],{"categories":3141},[82],{"categories":3143},[82],{"categories":3145},[47],{"categories":3147},[82],{"categories":3149},[82],{"categories":3151},[129],{"categories":3153},[95],{"categories":3155},[],{"categories":3157},[82],{"categories":3159},[82],{"categories":3161},[174],{"categories":3163},[82],{"categories":3165},[203],{"categories":3167},[95],{"categories":3169},[82],{"categories":3171},[95],{"categories":3173},[],{"categories":3175},[],{"categories":3177},[],{"categories":3179},[85],{"categories":3181},[129],{"categories":3183},[95],{"categories":3185},[82],{"categories":3187},[82],{"categories":3189},[82],{"categories":3191},[82],{"categories":3193},[355],{"categories":3195},[174],{"categories":3197},[95],{"categories":3199},[82],{"categories":3201},[],{"categories":3203},[95],{"categories":3205},[95],{"categories":3207},[],{"categories":3209},[82],{"categories":3211},[95],{"categories":3213},[82],{"categories":3215},[],{"categories":3217},[82],{"categories":3219},[82],{"categories":3221},[129],{"categories":3223},[174],{"categories":3225},[95],{"categories":3227},[174],{"categories":3229},[95],{"categories":3231},[82],{"categories":3233},[90],{"categories":3235},[],{"categories":3237},[],{"categories":3239},[82],{"categories":3241},[82],{"categories":3243},[85],{"categories":3245},[95],{"categories":3247},[129],{"categories":3249},[],{"categories":3251},[174],{"categories":3253},[],{"categories":3255},[107],{"categories":3257},[82],{"categories":3259},[107],{"categories":3261},[174],{"categories":3263},[107],{"categories":3265},[82],{"categories":3267},[],{"categories":3269},[82],{"categories":3271},[82],{"categories":3273},[],{"categories":3275},[82],{"categories":3277},[203],{"categories":3279},[82],{"categories":3281},[240],{"categories":3283},[107],{"categories":3285},[82],{"categories":3287},[],{"categories":3289},[95],{"categories":3291},[82],{"categories":3293},[85],{"categories":3295},[466],{"categories":3297},[82],{"categories":3299},[95],{"categories":3301},[82],{"categories":3303},[95],{"categories":3305},[82],{"categories":3307},[82],{"categories":3309},[82],{"categories":3311},[],{"categories":3313},[82],{"categories":3315},[85],{"categories":3317},[82],{"categories":3319},[90],{"categories":3321},[107],{"categories":3323},[174],{"categories":3325},[],{"categories":3327},[82],{"categories":3329},[],{"categories":3331},[],{"categories":3333},[95],{"categories":3335},[82],{"categories":3337},[107],{"categories":3339},[174],{"categories":3341},[129],{"categories":3343},[82],{"categories":3345},[129],{"categories":3347},[95],{"categories":3349},[174],{"categories":3351},[82],{"categories":3353},[],{"categories":3355},[82],{"categories":3357},[118],{"categories":3359},[95],{"categories":3361},[174],{"categories":3363},[129],{"categories":3365},[90],{"categories":3367},[107],{"categories":3369},[82],{"categories":3371},[82],{"categories":3373},[129],{"categories":3375},[203],{"categories":3377},[],{"categories":3379},[],{"categories":3381},[47],{"categories":3383},[411],{"categories":3385},[82],{"categories":3387},[95],{"categories":3389},[82,107],{"categories":3391},[129],{"categories":3393},[82],{"categories":3395},[82],{"categories":3397},[82],{"categories":3399},[82],{"categories":3401},[95],{"categories":3403},[82],{"categories":3405},[95],{"categories":3407},[82],{"categories":3409},[82],{"categories":3411},[82],{"categories":3413},[],{"categories":3415},[82],{"categories":3417},[1137],{"categories":3419},[107],{"categories":3421},[174],{"categories":3423},[82],{"categories":3425},[82],{"categories":3427},[82],{"categories":3429},[47],{"categories":3431},[95],{"categories":3433},[203],{"categories":3435},[240],{"categories":3437},[],{"categories":3439},[82],{"categories":3441},[90],{"categories":3443},[95],{"categories":3445},[85],{"categories":3447},[95],{"categories":3449},[82],{"categories":3451},[95],{"categories":3453},[95],{"categories":3455},[98],{"categories":3457},[107],{"categories":3459},[82],{"categories":3461},[82],{"categories":3463},[],{"categories":3465},[],{"categories":3467},[],{"categories":3469},[240],{"categories":3471},[82],{"categories":3473},[129],{"categories":3475},[82],{"categories":3477},[82],{"categories":3479},[82],{"categories":3481},[82],{"categories":3483},[],{"categories":3485},[82],{"categories":3487},[47],{"categories":3489},[90],{"categories":3491},[95],{"categories":3493},[82],{"categories":3495},[],{"categories":3497},[82],{"categories":3499},[95],{"categories":3501},[82],{"categories":3503},[240],{"categories":3505},[],{"categories":3507},[174],{"categories":3509},[174],{"categories":3511},[],{"categories":3513},[107],{"categories":3515},[82],{"categories":3517},[174],{"categories":3519},[82],{"categories":3521},[90],{"categories":3523},[95],{"categories":3525},[82],{"categories":3527},[],{"categories":3529},[129],{"categories":3531},[82],{"categories":3533},[82],{"categories":3535},[82],{"categories":3537},[174],{"categories":3539},[95],{"categories":3541},[129],{"categories":3543},[],{"categories":3545},[95],{"categories":3547},[90],{"categories":3549},[95],{"categories":3551},[174],{"categories":3553},[82],{"categories":3555},[82],{"categories":3557},[82],{"categories":3559},[411],{"categories":3561},[82],{"categories":3563},[],{"categories":3565},[82],{"categories":3567},[82],{"categories":3569},[240],{"categories":3571},[129],{"categories":3573},[47],{"categories":3575},[502],{"categories":3577},[47],{"categories":3579},[82],{"categories":3581},[],{"categories":3583},[],{"categories":3585},[],{"categories":3587},[95],{"categories":3589},[95],{"categories":3591},[107],{"categories":3593},[82],{"categories":3595},[388],{"categories":3597},[107],{"categories":3599},[82],{"categories":3601},[82],{"categories":3603},[82],{"categories":3605},[82],{"categories":3607},[95],{"categories":3609},[],{"categories":3611},[],{"categories":3613},[82],{"categories":3615},[],{"categories":3617},[82],{"categories":3619},[95],{"categories":3621},[174],{"categories":3623},[82],{"categories":3625},[82],{"categories":3627},[],{"categories":3629},[95],{"categories":3631},[98],{"categories":3633},[82],{"categories":3635},[174],{"categories":3637},[82],{"categories":3639},[95],{"categories":3641},[90],{"categories":3643},[82],{"categories":3645},[203],{"categories":3647},[95],{"categories":3649},[82],{"categories":3651},[82],{"categories":3653},[802],{"categories":3655},[82],{"categories":3657},[95],{"categories":3659},[82],{"categories":3661},[107],{"categories":3663},[82],{"categories":3665},[466],{"categories":3667},[174],{"categories":3669},[],{"categories":3671},[82],{"categories":3673},[129],{"categories":3675},[411],{"categories":3677},[95],{"categories":3679},[82],{"categories":3681},[],{"categories":3683},[129],{"categories":3685},[332],{"categories":3687},[95],{"categories":3689},[95],{"categories":3691},[95],{"categories":3693},[82],{"categories":3695},[82],{"categories":3697},[95],{"categories":3699},[],{"categories":3701},[90],{"categories":3703},[82],{"categories":3705},[90],{"categories":3707},[95],{"categories":3709},[],{"categories":3711},[107],{"categories":3713},[82],{"categories":3715},[82],{"categories":3717},[85],{"categories":3719},[129],{"categories":3721},[240],{"categories":3723},[118],{"categories":3725},[95],{"categories":3727},[95],{"categories":3729},[82],{"categories":3731},[95],{"categories":3733},[82],{"categories":3735},[85],{"categories":3737},[],{"categories":3739},[82],{"categories":3741},[82],{"categories":3743},[82],{"categories":3745},[95],{"categories":3747},[82],{"categories":3749},[],{"categories":3751},[],{"categories":3753},[174],{"categories":3755},[95],{"categories":3757},[82,90],{"categories":3759},[95],{"categories":3761},[82],{"categories":3763},[],{"categories":3765},[85],{"categories":3767},[47],{"categories":3769},[90],{"categories":3771},[82],{"categories":3773},[107],{"categories":3775},[82],{"categories":3777},[82],{"categories":3779},[95],{"categories":3781},[82],{"categories":3783},[82],{"categories":3785},[82],{"categories":3787},[129],{"categories":3789},[1137],{"categories":3791},[95],{"categories":3793},[82],{"categories":3795},[],{"categories":3797},[],{"categories":3799},[82],{"categories":3801},[95],{"categories":3803},[82],{"categories":3805},[82],{"categories":3807},[240],{"categories":3809},[],{"categories":3811},[82],{"categories":3813},[95],{"categories":3815},[118],{"categories":3817},[95],{"categories":3819},[411],{"categories":3821},[],{"categories":3823},[355],{"categories":3825},[95],{"categories":3827},[82],{"categories":3829},[203],{"categories":3831},[95],{"categories":3833},[82],{"categories":3835},[47],{"categories":3837},[98],{"categories":3839},[95],{"categories":3841},[82],{"categories":3843},[411],{"categories":3845},[82],{"categories":3847},[240],{"categories":3849},[],{"categories":3851},[82],{"categories":3853},[203],{"categories":3855},[174],{"categories":3857},[82],{"categories":3859},[82],{"categories":3861},[82],{"categories":3863},[],{"categories":3865},[203],{"categories":3867},[129],{"categories":3869},[82],{"categories":3871},[82],{"categories":3873},[82],{"categories":3875},[502],{"categories":3877},[85],{"categories":3879},[82],{"categories":3881},[82],{"categories":3883},[],{"categories":3885},[],{"categories":3887},[174],{"categories":3889},[82],{"categories":3891},[47],{"categories":3893},[203],{"categories":3895},[95],{"categories":3897},[82],{"categories":3899},[82],{"categories":3901},[203],{"categories":3903},[129],{"categories":3905},[],{"categories":3907},[82],{"categories":3909},[82],{"categories":3911},[],{"categories":3913},[82],{"categories":3915},[82],{"categories":3917},[527],{"categories":3919},[82],{"categories":3921},[82],{"categories":3923},[95],{"categories":3925},[107],{"categories":3927},[411],{"categories":3929},[82],{"categories":3931},[82],{"categories":3933},[82],{"categories":3935},[],{"categories":3937},[82,107],{"categories":3939},[129],{"categories":3941},[95],{"categories":3943},[107],{"categories":3945},[95],{"categories":3947},[838],{"categories":3949},[107],{"categories":3951},[95],{"categories":3953},[82],{"categories":3955},[85],{"categories":3957},[],{"categories":3959},[],{"categories":3961},[95],{"categories":3963},[82],{"categories":3965},[107],{"categories":3967},[82],{"categories":3969},[85],{"categories":3971},[107],{"categories":3973},[107],{"categories":3975},[82],{"categories":3977},[203],{"categories":3979},[82],{"categories":3981},[107],{"categories":3983},[82],{"categories":3985},[],{"categories":3987},[82],{"categories":3989},[174,82],{"categories":3991},[240],{"categories":3993},[85],{"categories":3995},[82],{"categories":3997},[],{"categories":3999},[82],{"categories":4001},[82],{"categories":4003},[90],{"categories":4005},[82],{"categories":4007},[90],{"categories":4009},[82],{"categories":4011},[82],{"categories":4013},[332],{"categories":4015},[82],{"categories":4017},[90],{"categories":4019},[107],{"categories":4021},[47],{"categories":4023},[95],{"categories":4025},[107],{"categories":4027},[82],{"categories":4029},[82],{"categories":4031},[129],{"categories":4033},[203],{"categories":4035},[174],{"categories":4037},[82],{"categories":4039},[82],{"categories":4041},[82],{"categories":4043},[82],{"categories":4045},[85],{"categories":4047},[82],{"categories":4049},[95],{"categories":4051},[95],{"categories":4053},[107],{"categories":4055},[129],{"categories":4057},[107],{"categories":4059},[107],{"categories":4061},[82],{"categories":4063},[82],{"categories":4065},[],{"categories":4067},[],{"categories":4069},[47],{"categories":4071},[82],{"categories":4073},[107],{"categories":4075},[82],{"categories":4077},[174],{"categories":4079},[411],{"categories":4081},[355],{"categories":4083},[332],{"categories":4085},[82],{"categories":4087},[82],{"categories":4089},[82],{"categories":4091},[47],{"categories":4093},[82],{"categories":4095},[82],{"categories":4097},[82],{"categories":4099},[82],{"categories":4101},[82],{"categories":4103},[82],{"categories":4105},[95],{"categories":4107},[85],{"categories":4109},[95],{"categories":4111},[82,90],{"categories":4113},[],{"categories":4115},[174],{"categories":4117},[],{"categories":4119},[98],{"categories":4121},[82],{"categories":4123},[129],{"categories":4125},[85],{"categories":4127},[82],{"categories":4129},[85],{"categories":4131},[95],{"categories":4133},[47],{"categories":4135},[95],{"categories":4137},[95],{"categories":4139},[82],{"categories":4141},[82],{"categories":4143},[90],{"categories":4145},[95],{"categories":4147},[107],{"categories":4149},[203],{"categories":4151},[82],{"categories":4153},[],{"categories":4155},[129],{"categories":4157},[82],{"categories":4159},[82],{"categories":4161},[82],{"categories":4163},[82],{"categories":4165},[82],{"categories":4167},[82],{"categories":4169},[107],{"categories":4171},[129],{"categories":4173},[107],{"categories":4175},[107],{"categories":4177},[82],{"categories":4179},[82],{"categories":4181},[82],{"categories":4183},[355],{"categories":4185},[82],{"categories":4187},[95],{"categories":4189},[129],{"categories":4191},[82],{"categories":4193},[82],{"categories":4195},[82],{"categories":4197},[95],{"categories":4199},[82],{"categories":4201},[82],{"categories":4203},[82],{"categories":4205},[2906],{"categories":4207},[4208],"Clinical AI",{"categories":4210},[174],{"categories":4212},[82],{"categories":4214},[82],{"categories":4216},[82],{"categories":4218},[240],{"categories":4220},[2305],{"categories":4222},[82],{"categories":4224},[98],{"categories":4226},[82],{"categories":4228},[95],{"categories":4230},[82],{"categories":4232},[82],{"categories":4234},[129],{"categories":4236},[82],{"categories":4238},[95],{"categories":4240},[107],{"categories":4242},[203],{"categories":4244},[82],{"categories":4246},[82],{"categories":4248},[90],{"categories":4250},[82],{"categories":4252},[82],{"categories":4254},[466],{"categories":4256},[82],{"categories":4258},[],{"categories":4260},[82],{"categories":4262},[107],{"categories":4264},[85],{"categories":4266},[82],{"categories":4268},[],{"categories":4270},[],{"categories":4272},[82],{"categories":4274},[],{"categories":4276},[90],{"categories":4278},[82],{"categories":4280},[82],{"categories":4282},[95],{"categories":4284},[129],{"categories":4286},[129],{"categories":4288},[129],{"categories":4290},[129],{"categories":4292},[],{"categories":4294},[85],{"categories":4296},[95],{"categories":4298},[129],{"categories":4300},[82],{"categories":4302},[527],{"categories":4304},[98],{"categories":4306},[82],{"categories":4308},[85],{"categories":4310},[82],{"categories":4312},[95],{"categories":4314},[82],{"categories":4316},[82],{"categories":4318},[82,95],{"categories":4320},[95],{"categories":4322},[240],{"categories":4324},[129],{"categories":4326},[95],{"categories":4328},[129],{"categories":4330},[95],{"categories":4332},[82],{"categories":4334},[],{"categories":4336},[129],{"categories":4338},[203],{"categories":4340},[85],{"categories":4342},[82],{"categories":4344},[82],{"categories":4346},[],{"categories":4348},[107],{"categories":4350},[],{"categories":4352},[85],{"categories":4354},[95],{"categories":4356},[129],{"categories":4358},[82],{"categories":4360},[129],{"categories":4362},[85],{"categories":4364},[129],{"categories":4366},[129],{"categories":4368},[],{"categories":4370},[90],{"categories":4372},[95],{"categories":4374},[129],{"categories":4376},[129],{"categories":4378},[129],{"categories":4380},[129],{"categories":4382},[129],{"categories":4384},[129],{"categories":4386},[129],{"categories":4388},[129],{"categories":4390},[129],{"categories":4392},[129],{"categories":4394},[47],{"categories":4396},[85],{"categories":4398},[82],{"categories":4400},[82],{"categories":4402},[95],{"categories":4404},[95],{"categories":4406},[],{"categories":4408},[82],{"categories":4410},[82,85],{"categories":4412},[],{"categories":4414},[95],{"categories":4416},[82],{"categories":4418},[129],{"categories":4420},[95],{"categories":4422},[838],{"categories":4424},[82],{"categories":4426},[82],{"categories":4428},[82],{"categories":4430},[82],{"categories":4432},[82],{"categories":4434},[332],{"categories":4436},[82],{"categories":4438},[82],{"categories":4440},[95],{"categories":4442},[82],{"categories":4444},[90],{"categories":4446},[98],{"categories":4448},[95],{"categories":4450},[95],{"categories":4452},[],{"categories":4454},[95],{"categories":4456},[174],{"categories":4458},[129],{"categories":4460},[82],{"categories":4462},[],{"categories":4464},[98],{"categories":4466},[],{"categories":4468},[107],{"categories":4470},[95],{"categories":4472},[174],{"categories":4474},[82],{"categories":4476},[],{"categories":4478},[82],{"categories":4480},[],{"categories":4482},[203],{"categories":4484},[82],{"categories":4486},[],{"categories":4488},[],{"categories":4490},[129],{"categories":4492},[85],{"categories":4494},[82],{"categories":4496},[82],{"categories":4498},[90],{"categories":4500},[82],{"categories":4502},[82],{"categories":4504},[82],{"categories":4506},[90],{"categories":4508},[90],{"categories":4510},[174],{"categories":4512},[],{"categories":4514},[82],{"categories":4516},[129],{"categories":4518},[],{"categories":4520},[82],{"categories":4522},[82],{"categories":4524},[174],{"categories":4526},[82],{"categories":4528},[203],{"categories":4530},[82],{"categories":4532},[240],{"categories":4534},[],{"categories":4536},[95],{"categories":4538},[203],{"categories":4540},[107],{"categories":4542},[],{"categories":4544},[82],{"categories":4546},[],{"categories":4548},[95],{"categories":4550},[174],{"categories":4552},[107],{"categories":4554},[],{"categories":4556},[2906],{"categories":4558},[90],{"categories":4560},[85],{"categories":4562},[82],{"categories":4564},[47],{"categories":4566},[95],{"categories":4568},[174],{"categories":4570},[107],{"categories":4572},[],{"categories":4574},[],{"categories":4576},[82],{"categories":4578},[85],{"categories":4580},[82],{"categories":4582},[203],{"categories":4584},[],{"categories":4586},[95],{"categories":4588},[95],{"categories":4590},[82],{"categories":4592},[95],{"categories":4594},[82],{"categories":4596},[129],{"categories":4598},[107],{"categories":4600},[82],{"categories":4602},[95],{"categories":4604},[98],{"categories":4606},[82],{"categories":4608},[82],{"categories":4610},[95],{"categories":4612},[82],{"categories":4614},[98],{"categories":4616},[203],{"categories":4618},[129],{"categories":4620},[],{"categories":4622},[203],{"categories":4624},[82],{"categories":4626},[],{"categories":4628},[107],{"categories":4630},[95],{"categories":4632},[],{"categories":4634},[82],{"categories":4636},[82],{"categories":4638},[82],{"categories":4640},[82],{"categories":4642},[82],{"categories":4644},[95],{"categories":4646},[90],{"categories":4648},[85],{"categories":4650},[82],{"categories":4652},[174],{"categories":4654},[107],{"categories":4656},[107],{"categories":4658},[82],{"categories":4660},[47],{"categories":4662},[95],{"categories":4664},[82],{"categories":4666},[82],{"categories":4668},[95],{"categories":4670},[82],{"categories":4672},[90],{"categories":4674},[174],{"categories":4676},[107],{"categories":4678},[95],{"categories":4680},[82],{"categories":4682},[98],{"categories":4684},[82],{"categories":4686},[95],{"categories":4688},[82],{"categories":4690},[82],{"categories":4692},[129],{"categories":4694},[82],{"categories":4696},[],{"categories":4698},[85],{"categories":4700},[82],{"categories":4702},[82],{"categories":4704},[82],{"categories":4706},[107],{"categories":4708},[107],{"categories":4710},[82],{"categories":4712},[107],{"categories":4714},[82],{"categories":4716},[95],{"categories":4718},[82],{"categories":4720},[82],{"categories":4722},[82],{"categories":4724},[82],{"categories":4726},[82],{"categories":4728},[],{"categories":4730},[82],{"categories":4732},[174],{"categories":4734},[90],{"categories":4736},[129],{"categories":4738},[82],{"categories":4740},[95],{"categories":4742},[82],{"categories":4744},[95],{"categories":4746},[82],{"categories":4748},[82],{"categories":4750},[174],{"categories":4752},[95],{"categories":4754},[82],{"categories":4756},[203],{"categories":4758},[82],{"categories":4760},[47],{"categories":4762},[82],{"categories":4764},[82],{"categories":4766},[129],{"categories":4768},[82],{"categories":4770},[82],{"categories":4772},[82],{"categories":4774},[82],{"categories":4776},[95],{"categories":4778},[240],{"categories":4780},[82],{"categories":4782},[107],{"categories":4784},[95],{"categories":4786},[47],{"categories":4788},[],{"categories":4790},[95],{"categories":4792},[107],{"categories":4794},[82],{"categories":4796},[82],{"categories":4798},[2151],{"categories":4800},[174],{"categories":4802},[269],{"categories":4804},[82],{"categories":4806},[82],{"categories":4808},[82],{"categories":4810},[82],{"categories":4812},[85],{"categories":4814},[82],{"categories":4816},[82],{"categories":4818},[107],{"categories":4820},[90],{"categories":4822},[107],{"categories":4824},[82],{"categories":4826},[],{"categories":4828},[95],{"categories":4830},[95],{"categories":4832},[82],{"categories":4834},[82],{"categories":4836},[47],{"categories":4838},[],{"categories":4840},[129],{"categories":4842},[],{"categories":4844},[129],{"categories":4846},[82],{"categories":4848},[82],{"categories":4850},[95],{"categories":4852},[82],{"categories":4854},[95],{"categories":4856},[95],{"categories":4858},[],{"categories":4860},[129],{"categories":4862},[82],{"categories":4864},[],{"categories":4866},[82],{"categories":4868},[82],{"categories":4870},[],{"categories":4872},[82],{"categories":4874},[174],{"categories":4876},[107],{"categories":4878},[95],{"categories":4880},[82],{"categories":4882},[82],{"categories":4884},[82],{"categories":4886},[203],{"categories":4888},[82],{"categories":4890},[82],{"categories":4892},[82],{"categories":4894},[85],{"categories":4896},[82],{"categories":4898},[82],{"categories":4900},[],{"categories":4902},[82],{"categories":4904},[82],{"categories":4906},[],{"categories":4908},[85],{"categories":4910},[82],{"categories":4912},[129],{"categories":4914},[107],{"categories":4916},[98],{"categories":4918},[411],{"categories":4920},[82],{"categories":4922},[82],{"categories":4924},[82],{"categories":4926},[107],{"categories":4928},[129],{"categories":4930},[174],{"categories":4932},[82],{"categories":4934},[82],{"categories":4936},[82],{"categories":4938},[82],{"categories":4940},[129],{"categories":4942},[174],{"categories":4944},[82],{"categories":4946},[82],{"categories":4948},[129],{"categories":4950},[174],{"categories":4952},[82],{"categories":4954},[129],{"categories":4956},[82],{"categories":4958},[95],{"categories":4960},[95],{"categories":4962},[95],{"categories":4964},[107],{"categories":4966},[129],{"categories":4968},[95],{"categories":4970},[95],{"categories":4972},[82],{"categories":4974},[107],{"categories":4976},[174],{"categories":4978},[82],{"categories":4980},[82],{"categories":4982},[82],{"categories":4984},[],{"categories":4986},[95],{"categories":4988},[],{"categories":4990},[82],{"categories":4992},[82],{"categories":4994},[],{"categories":4996},[],{"categories":4998},[95],{"categories":5000},[90],{"categories":5002},[95],{"categories":5004},[5005],"Liability & Ethics",{"categories":5007},[82],{"categories":5009},[82],{"categories":5011},[95],{"categories":5013},[85],{"categories":5015},[95],{"categories":5017},[90],{"categories":5019},[203],{"categories":5021},[95],{"categories":5023},[82],{"categories":5025},[82],{"categories":5027},[],{"categories":5029},[502],{"categories":5031},[95],{"categories":5033},[],{"categories":5035},[82],{"categories":5037},[85],{"categories":5039},[95],{"categories":5041},[],{"categories":5043},[95],{"categories":5045},[82],{"categories":5047},[82],{"categories":5049},[107],{"categories":5051},[82],{"categories":5053},[129],{"categories":5055},[82],{"categories":5057},[82],{"categories":5059},[95],{"categories":5061},[82],{"categories":5063},[82],{"categories":5065},[82],{"categories":5067},[129],{"categories":5069},[95],{"categories":5071},[107],{"categories":5073},[174],{"categories":5075},[85],{"categories":5077},[82],{"categories":5079},[82],{"categories":5081},[],{"categories":5083},[95],{"categories":5085},[95],{"categories":5087},[95],{"categories":5089},[411],{"categories":5091},[174],{"categories":5093},[95],{"categories":5095},[240],{"categories":5097},[107],{"categories":5099},[129],{"categories":5101},[82],{"categories":5103},[174],{"categories":5105},[82],{"categories":5107},[85],{"categories":5109},[],{"categories":5111},[95],{"categories":5113},[82],{"categories":5115},[82],{"categories":5117},[82],{"categories":5119},[95],{"categories":5121},[82],{"categories":5123},[174],{"categories":5125},[],{"categories":5127},[95],{"categories":5129},[98],{"categories":5131},[129],{"categories":5133},[95],{"categories":5135},[90],{"categories":5137},[],{"categories":5139},[82],{"categories":5141},[82],{"categories":5143},[98],{"categories":5145},[82],{"categories":5147},[95],{"categories":5149},[129],{"categories":5151},[85],{"categories":5153},[240],{"categories":5155},[82],{"categories":5157},[82],{"categories":5159},[82],{"categories":5161},[129],{"categories":5163},[90],{"categories":5165},[82],{"categories":5167},[174],{"categories":5169},[129],{"categories":5171},[240],{"categories":5173},[82],{"categories":5175},[95],{"categories":5177},[],{"categories":5179},[466],{"categories":5181},[],{"categories":5183},[82],{"categories":5185},[240],{"categories":5187},[82],{"categories":5189},[47],{"categories":5191},[95],{"categories":5193},[95],{"categories":5195},[5196],"Design News & Tools",{"categories":5198},[82],{"categories":5200},[129],{"categories":5202},[82],{"categories":5204},[82],{"categories":5206},[85],{"categories":5208},[82],{"categories":5210},[174],{"categories":5212},[95],{"categories":5214},[95],{"categories":5216},[174],{"categories":5218},[82],{"categories":5220},[411],{"categories":5222},[95],{"categories":5224},[82],{"categories":5226},[82],{"categories":5228},[411],{"categories":5230},[82],{"categories":5232},[203],{"categories":5234},[82],{"categories":5236},[95],{"categories":5238},[],{"categories":5240},[82],{"categories":5242},[82],{"categories":5244},[82],{"categories":5246},[129],{"categories":5248},[85],{"categories":5250},[],{"categories":5252},[82],{"categories":5254},[82],{"categories":5256},[82],{"categories":5258},[107],{"categories":5260},[527],{"categories":5262},[107],{"categories":5264},[174],{"categories":5266},[82],{"categories":5268},[82,95],{"categories":5270},[203,90],{"categories":5272},[107],{"categories":5274},[82],{"categories":5276},[82],{"categories":5278},[82],{"categories":5280},[82],{"categories":5282},[],{"categories":5284},[95],{"categories":5286},[82],{"categories":5288},[],{"categories":5290},[82],{"categories":5292},[107],{"categories":5294},[82],{"categories":5296},[107],{"categories":5298},[],{"categories":5300},[95],{"categories":5302},[82],{"categories":5304},[90],{"categories":5306},[82],{"categories":5308},[129],{"categories":5310},[82],{"categories":5312},[],{"categories":5314},[95],{"categories":5316},[82],{"categories":5318},[],{"categories":5320},[174],{"categories":5322},[82],{"categories":5324},[82],{"categories":5326},[95],{"categories":5328},[82],{"categories":5330},[82],{"categories":5332},[85],{"categories":5334},[95],{"categories":5336},[82],{"categories":5338},[],{"categories":5340},[240],{"categories":5342},[203],{"categories":5344},[90],{"categories":5346},[90],{"categories":5348},[82],{"categories":5350},[85],{"categories":5352},[85],{"categories":5354},[82],{"categories":5356},[95],{"categories":5358},[82],{"categories":5360},[82],{"categories":5362},[82],{"categories":5364},[82],{"categories":5366},[107],{"categories":5368},[82],{"categories":5370},[85],{"categories":5372},[82],{"categories":5374},[95],{"categories":5376},[82],{"categories":5378},[203],{"categories":5380},[82],{"categories":5382},[129],{"categories":5384},[82],{"categories":5386},[82],{"categories":5388},[95],{"categories":5390},[82],{"categories":5392},[95],{"categories":5394},[],{"categories":5396},[107],{"categories":5398},[],{"categories":5400},[107],{"categories":5402},[95],{"categories":5404},[85],{"categories":5406},[],{"categories":5408},[47],{"categories":5410},[240],{"categories":5412},[82],{"categories":5414},[107],{"categories":5416},[82],{"categories":5418},[],{"categories":5420},[129],{"categories":5422},[95],{"categories":5424},[107],{"categories":5426},[174],{"categories":5428},[82],{"categories":5430},[82],{"categories":5432},[95],{"categories":5434},[107],{"categories":5436},[95],{"categories":5438},[129],{"categories":5440},[82],{"categories":5442},[98],{"categories":5444},[85],{"categories":5446},[98],{"categories":5448},[129],{"categories":5450},[82],{"categories":5452},[107],{"categories":5454},[82],{"categories":5456},[174],{"categories":5458},[90],{"categories":5460},[82],{"categories":5462},[82],{"categories":5464},[82],{"categories":5466},[82],{"categories":5468},[82],{"categories":5470},[82],{"categories":5472},[95],{"categories":5474},[82],{"categories":5476},[95],{"categories":5478},[82],{"categories":5480},[82],{"categories":5482},[85],{"categories":5484},[82],{"categories":5486},[95],{"categories":5488},[95],{"categories":5490},[174],{"categories":5492},[95],{"categories":5494},[95],{"categories":5496},[85],{"categories":5498},[95],{"categories":5500},[174],{"categories":5502},[],{"categories":5504},[82],{"categories":5506},[47],{"categories":5508},[411],{"categories":5510},[82],{"categories":5512},[82],{"categories":5514},[82],{"categories":5516},[107],{"categories":5518},[82],{"categories":5520},[],{"categories":5522},[82],{"categories":5524},[95],{"categories":5526},[82],{"categories":5528},[203],{"categories":5530},[82],{"categories":5532},[129],{"categories":5534},[95],{"categories":5536},[82],{"categories":5538},[203],{"categories":5540},[95],{"categories":5542},[90],{"categories":5544},[90],{"categories":5546},[82],{"categories":5548},[82],{"categories":5550},[82],{"categories":5552},[82],{"categories":5554},[82],{"categories":5556},[85],{"categories":5558},[],{"categories":5560},[82],{"categories":5562},[82],{"categories":5564},[95],{"categories":5566},[95],{"categories":5568},[82],{"categories":5570},[82],{"categories":5572},[82],{"categories":5574},[107],{"categories":5576},[],{"categories":5578},[85],{"categories":5580},[82],{"categories":5582},[82],{"categories":5584},[95],{"categories":5586},[95],{"categories":5588},[],{"categories":5590},[107],{"categories":5592},[107],{"categories":5594},[82],{"categories":5596},[203],{"categories":5598},[90],{"categories":5600},[174],{"categories":5602},[],{"categories":5604},[82],{"categories":5606},[95],{"categories":5608},[85],{"categories":5610},[82],{"categories":5612},[82],{"categories":5614},[107],{"categories":5616},[85],{"categories":5618},[82],{"categories":5620},[82],{"categories":5622},[129],{"categories":5624},[47],{"categories":5626},[129],{"categories":5628},[95],{"categories":5630},[82],{"categories":5632},[],{"categories":5634},[129],{"categories":5636},[95],{"categories":5638},[174],{"categories":5640},[47],{"categories":5642},[82],{"categories":5644},[82],{"categories":5646},[],{"categories":5648},[95],{"categories":5650},[95],{"categories":5652},[95],{"categories":5654},[2906],{"categories":5656},[129],{"categories":5658},[82],{"categories":5660},[107],{"categories":5662},[82],{"categories":5664},[82],{"categories":5666},[82],{"categories":5668},[82],{"categories":5670},[90],{"categories":5672},[82],{"categories":5674},[85],{"categories":5676},[1667],{"categories":5678},[240],{"categories":5680},[85],{"categories":5682},[],{"categories":5684},[82],{"categories":5686},[],{"categories":5688},[129],{"categories":5690},[95],{"categories":5692},[174],{"categories":5694},[82],{"categories":5696},[82],{"categories":5698},[129],{"categories":5700},[],{"categories":5702},[95],{"categories":5704},[95],{"categories":5706},[95],{"categories":5708},[],{"categories":5710},[82],{"categories":5712},[],{"categories":5714},[129],{"categories":5716},[85],{"categories":5718},[174],{"categories":5720},[82],{"categories":5722},[95],{"categories":5724},[129],{"categories":5726},[82],{"categories":5728},[129],{"categories":5730},[],{"categories":5732},[129],{"categories":5734},[85],{"categories":5736},[411],{"categories":5738},[95],{"categories":5740},[82],{"categories":5742},[],{"categories":5744},[107],{"categories":5746},[95],{"categories":5748},[98],{"categories":5750},[95],{"categories":5752},[85],{"categories":5754},[],{"categories":5756},[],{"categories":5758},[],{"categories":5760},[174],{"categories":5762},[95],{"categories":5764},[82],{"categories":5766},[82],{"categories":5768},[],{"categories":5770},[],{"categories":5772},[],{"categories":5774},[82],{"categories":5776},[174],{"categories":5778},[82],{"categories":5780},[],{"categories":5782},[95],{"categories":5784},[82],{"categories":5786},[82],{"categories":5788},[85],{"categories":5790},[],{"categories":5792},[],{"categories":5794},[82],{"categories":5796},[174],{"categories":5798},[82],{"categories":5800},[129],{"categories":5802},[],{"categories":5804},[82],{"categories":5806},[203],{"categories":5808},[129],{"categories":5810},[203],{"categories":5812},[47],{"categories":5814},[82],{"categories":5816},[82],{"categories":5818},[],{"categories":5820},[],{"categories":5822},[95],{"categories":5824},[],{"categories":5826},[82],{"categories":5828},[411],{"categories":5830},[82],{"categories":5832},[82],{"categories":5834},[82],{"categories":5836},[82],{"categories":5838},[],{"categories":5840},[95],{"categories":5842},[82],{"categories":5844},[82],{"categories":5846},[],{"categories":5848},[95],{"categories":5850},[82],{"categories":5852},[129],{"categories":5854},[82],{"categories":5856},[203],{"categories":5858},[90],{"categories":5860},[82],{"categories":5862},[82],{"categories":5864},[95],{"categories":5866},[47],{"categories":5868},[95],{"categories":5870},[95],{"categories":5872},[],{"categories":5874},[95],{"categories":5876},[],{"categories":5878},[82],{"categories":5880},[],{"categories":5882},[129],{"categories":5884},[90],{"categories":5886},[],{"categories":5888},[82],{"categories":5890},[82],{"categories":5892},[],{"categories":5894},[174],{"categories":5896},[85],{"categories":5898},[],{"categories":5900},[90],{"categories":5902},[203],{"categories":5904},[82],{"categories":5906},[107],{"categories":5908},[85],{"categories":5910},[47],{"categories":5912},[90],{"categories":5914},[107],{"categories":5916},[95],{"categories":5918},[107],{"categories":5920},[],{"categories":5922},[82],{"categories":5924},[98],{"categories":5926},[82],{"categories":5928},[],{"categories":5930},[95],{"categories":5932},[85],{"categories":5934},[174],{"categories":5936},[82],{"categories":5938},[85],{"categories":5940},[95],{"categories":5942},[240],{"categories":5944},[82],{"categories":5946},[82],{"categories":5948},[82],{"categories":5950},[85],{"categories":5952},[47],{"categories":5954},[95],{"categories":5956},[],{"categories":5958},[82],{"categories":5960},[82],{"categories":5962},[82],{"categories":5964},[107],{"categories":5966},[95],{"categories":5968},[129],{"categories":5970},[107],{"categories":5972},[82],{"categories":5974},[98],{"categories":5976},[],{"categories":5978},[174],{"categories":5980},[107],{"categories":5982},[129],{"categories":5984},[85],{"categories":5986},[95],{"categories":5988},[82],{"categories":5990},[82],{"categories":5992},[95],{"categories":5994},[98],{"categories":5996},[82],{"categories":5998},[95],{"categories":6000},[82],{"categories":6002},[90],{"categories":6004},[95],{"categories":6006},[95,240],{"categories":6008},[82],{"categories":6010},[82],{"categories":6012},[95],{"categories":6014},[107],{"categories":6016},[82],{"categories":6018},[82],{"categories":6020},[47],{"categories":6022},[95],{"categories":6024},[203],{"categories":6026},[95],{"categories":6028},[90],{"categories":6030},[],{"categories":6032},[95],{"categories":6034},[82],{"categories":6036},[90],{"categories":6038},[],{"categories":6040},[],{"categories":6042},[107],{"categories":6044},[82],{"categories":6046},[82],{"categories":6048},[95],{"categories":6050},[47],{"categories":6052},[203],{"categories":6054},[82],{"categories":6056},[82],{"categories":6058},[95],{"categories":6060},[],{"categories":6062},[95],{"categories":6064},[129],{"categories":6066},[95],{"categories":6068},[82],{"categories":6070},[],{"categories":6072},[129],{"categories":6074},[107],{"categories":6076},[2906],{"categories":6078},[85],{"categories":6080},[107],{"categories":6082},[82],{"categories":6084},[95],{"categories":6086},[82],{"categories":6088},[82],{"categories":6090},[203],{"categories":6092},[107],{"categories":6094},[],{"categories":6096},[129],{"categories":6098},[82],{"categories":6100},[],{"categories":6102},[95],{"categories":6104},[82],{"categories":6106},[82],{"categories":6108},[82],{"categories":6110},[82],{"categories":6112},[95],{"categories":6114},[82],{"categories":6116},[82],{"categories":6118},[98],{"categories":6120},[82],{"categories":6122},[95],{"categories":6124},[82],{"categories":6126},[82],{"categories":6128},[82],{"categories":6130},[82],{"categories":6132},[82],{"categories":6134},[82],{"categories":6136},[82],{"categories":6138},[90],{"categories":6140},[],{"categories":6142},[98],{"categories":6144},[129],{"categories":6146},[95],{"categories":6148},[82],{"categories":6150},[107],{"categories":6152},[],{"categories":6154},[107],{"categories":6156},[107],{"categories":6158},[95],{"categories":6160},[107],{"categories":6162},[82],{"categories":6164},[82],{"categories":6166},[82],{"categories":6168},[95],{"categories":6170},[107],{"categories":6172},[82],{"categories":6174},[82],{"categories":6176},[82],{"categories":6178},[95],{"categories":6180},[129],{"categories":6182},[82],{"categories":6184},[82],{"categories":6186},[82],{"categories":6188},[90],{"categories":6190},[82],{"categories":6192},[95],{"categories":6194},[174],{"categories":6196},[],{"categories":6198},[82],{"categories":6200},[47],{"categories":6202},[95],{"categories":6204},[82],{"categories":6206},[82],{"categories":6208},[],{"categories":6210},[82],{"categories":6212},[82],{"categories":6214},[129],{"categories":6216},[82],{"categories":6218},[82],{"categories":6220},[95],{"categories":6222},[203],{"categories":6224},[],{"categories":6226},[],{"categories":6228},[107],{"categories":6230},[82],{"categories":6232},[129],{"categories":6234},[82],{"categories":6236},[107],{"categories":6238},[129],{"categories":6240},[82],{"categories":6242},[203],{"categories":6244},[47],{"categories":6246},[82],{"categories":6248},[82],{"categories":6250},[85],{"categories":6252},[95],{"categories":6254},[82],{"categories":6256},[82],{"categories":6258},[95],{"categories":6260},[95],{"categories":6262},[82],{"categories":6264},[90],{"categories":6266},[],{"categories":6268},[47],{"categories":6270},[82],{"categories":6272},[],{"categories":6274},[129],{"categories":6276},[82],{"categories":6278},[47],{"categories":6280},[82],{"categories":6282},[107],{"categories":6284},[107],{"categories":6286},[107],{"categories":6288},[95],{"categories":6290},[95],{"categories":6292},[82],{"categories":6294},[95],{"categories":6296},[82],{"categories":6298},[82],{"categories":6300},[174],{"categories":6302},[47],{"categories":6304},[47],{"categories":6306},[],{"categories":6308},[129],{"categories":6310},[82],{"categories":6312},[82],{"categories":6314},[107],{"categories":6316},[],{"categories":6318},[129],{"categories":6320},[129],{"categories":6322},[129],{"categories":6324},[],{"categories":6326},[95],{"categories":6328},[82],{"categories":6330},[],{"categories":6332},[85],{"categories":6334},[90],{"categories":6336},[],{"categories":6338},[82],{"categories":6340},[82],{"categories":6342},[],{"categories":6344},[107],{"categories":6346},[],{"categories":6348},[],{"categories":6350},[],{"categories":6352},[],{"categories":6354},[82],{"categories":6356},[129],{"categories":6358},[],{"categories":6360},[],{"categories":6362},[82],{"categories":6364},[82],{"categories":6366},[82],{"categories":6368},[47],{"categories":6370},[82],{"categories":6372},[47],{"categories":6374},[],{"categories":6376},[47],{"categories":6378},[47],{"categories":6380},[240],{"categories":6382},[95],{"categories":6384},[107],{"categories":6386},[],{"categories":6388},[],{"categories":6390},[47],{"categories":6392},[107],{"categories":6394},[107],{"categories":6396},[107],{"categories":6398},[],{"categories":6400},[85],{"categories":6402},[107],{"categories":6404},[107],{"categories":6406},[85],{"categories":6408},[107],{"categories":6410},[90],{"categories":6412},[107],{"categories":6414},[107],{"categories":6416},[107],{"categories":6418},[47],{"categories":6420},[129],{"categories":6422},[129],{"categories":6424},[82],{"categories":6426},[107],{"categories":6428},[47],{"categories":6430},[240],{"categories":6432},[47],{"categories":6434},[47],{"categories":6436},[47],{"categories":6438},[],{"categories":6440},[90],{"categories":6442},[],{"categories":6444},[240],{"categories":6446},[107],{"categories":6448},[107],{"categories":6450},[107],{"categories":6452},[95],{"categories":6454},[129,90],{"categories":6456},[47],{"categories":6458},[],{"categories":6460},[],{"categories":6462},[47],{"categories":6464},[],{"categories":6466},[47],{"categories":6468},[129],{"categories":6470},[95],{"categories":6472},[],{"categories":6474},[107],{"categories":6476},[82],{"categories":6478},[174],{"categories":6480},[],{"categories":6482},[82],{"categories":6484},[],{"categories":6486},[129],{"categories":6488},[85],{"categories":6490},[47],{"categories":6492},[],{"categories":6494},[107],{"categories":6496},[129],[6498,6549,6597,6652],{"id":6499,"title":6500,"ai":6501,"body":6507,"categories":6535,"created_at":48,"date_modified":48,"description":40,"extension":49,"faq":48,"featured":50,"kicker_label":48,"meta":6536,"navigation":63,"path":6537,"published_at":6538,"question":48,"scraped_at":48,"seo":6539,"sitemap":6540,"source_id":6541,"source_name":6542,"source_type":70,"source_url":6543,"stem":6544,"tags":6545,"thumbnail_url":48,"tldr":6546,"tweet":48,"unknown_tags":6547,"__hash__":6548},"summaries\u002Fsummaries\u002Fstatic-embeddings-fail-on-context-dependent-meanin-summary.md","Static Embeddings Fail on Context-Dependent Meaning",{"provider":7,"model":6502,"input_tokens":6503,"output_tokens":6504,"processing_time_ms":6505,"cost_usd":6506},"x-ai\u002Fgrok-4.1-fast",5723,1321,9367,0.00178245,{"type":14,"value":6508,"toc":6530},[6509,6513,6516,6520,6523,6527],[17,6510,6512],{"id":6511},"static-embeddings-breakthrough-and-core-limitation","Static Embeddings' Breakthrough and Core Limitation",[22,6514,6515],{},"Word2Vec transformed NLP by assigning words stable vectors based on their 'neighbors' in training data, placing similar concepts like 'king'-'queen' or 'Paris'-'London' near each other in semantic space. This represented relationships, not just frequencies, turning words into positions with preserved meaning. However, it assumes one vector per word captures its overall sense—a blended average across uses—which loses precision for polysemous words. 'Bank' gets a single vector mixing riverbank and financial institution traits, preventing clean disambiguation: \"She sat on the bank\" (river edge) vs. \"She went to the bank\" (loan office). Same for 'light' (illumination\u002Fweight), 'bat' (animal\u002Fsports gear), 'duck' (bird\u002Faction), and 'cold' (temperature\u002Fillness\u002Fdistance). Impact: Models make shallow decisions in translation, QA, summarization, search, and dialogue, as they can't activate the exact sense.",[17,6517,6519],{"id":6518},"context-activates-and-shapes-meaning","Context Activates and Shapes Meaning",[22,6521,6522],{},"Words aren't self-contained; they trigger potential meanings refined by surrounding context. 'He is cold' could mean temperature or emotional distance, but 'The weather is cold' collapses ambiguity to temperature. Static vectors capture general neighborhoods but not sentence-specific interpretation—'Apple' as fruit or company shifts with \"She sliced the apple\" vs. \"Apple launched a product.\" Sequence order amplifies this: 'dog bites man' vs. 'man bites dog' inverts meaning despite identical words. Language unfolds sequentially, requiring models to carry 'unfolding memory' where prior words influence later ones. Without this, representation stays isolated, ignoring how context dynamically selects and updates meaning.",[17,6524,6526],{"id":6525},"transition-to-dynamic-sequence-models","Transition to Dynamic Sequence Models",[22,6528,6529],{},"This gap exposed that language understanding demands more than static semantics—models need to process evolving streams, remembering prior context to shape interpretation. Static embeddings enabled word-level relationships; contextual representations enable sentence-level dynamics. This pressure birthed recurrent models with hidden states for sequence memory, leading to LSTMs, encoder-decoders, attention, and transformers. Outcomes: Machines track precise, unfolding meaning, enabling robust downstream tasks. Word2Vec marked words becoming representable; the next era gave meanings 'motion' through context.",{"title":40,"searchDepth":41,"depth":41,"links":6531},[6532,6533,6534],{"id":6511,"depth":41,"text":6512},{"id":6518,"depth":41,"text":6519},{"id":6525,"depth":41,"text":6526},[],{},"\u002Fsummaries\u002Fstatic-embeddings-fail-on-context-dependent-meanin-summary","2026-04-08 21:21:18",{"title":6500,"description":40},{"loc":6537},"71ab26e32ef8c9d0","Towards AI","https:\u002F\u002Funknown","summaries\u002Fstatic-embeddings-fail-on-context-dependent-meanin-summary",[74,75],"Word2Vec captured general word relationships but couldn't handle polysemy or sequence, like 'bank' shifting from river to finance based on context—forcing NLP to dynamic models.",[75],"wRvRTpKiycxG5K5fn9XYJnSIjMgKwb1BwcGEYi9Rcms",{"id":6550,"title":6551,"ai":6552,"body":6557,"categories":6577,"created_at":48,"date_modified":48,"description":40,"extension":49,"faq":48,"featured":50,"kicker_label":48,"meta":6578,"navigation":63,"path":6586,"published_at":6587,"question":48,"scraped_at":6587,"seo":6588,"sitemap":6589,"source_id":6590,"source_name":69,"source_type":70,"source_url":6582,"stem":6591,"tags":6592,"thumbnail_url":48,"tldr":6594,"tweet":48,"unknown_tags":6595,"__hash__":6596},"summaries\u002Fsummaries\u002F11f943a4cc8b55bd-midas-handling-incomplete-multimodal-sentiment-ana-summary.md","MIDAS: Handling Incomplete Multimodal Sentiment Analysis",{"provider":7,"model":8,"input_tokens":6553,"output_tokens":6554,"processing_time_ms":6555,"cost_usd":6556},4033,468,2586,0.00171025,{"type":14,"value":6558,"toc":6573},[6559,6563,6566,6570],[17,6560,6562],{"id":6561},"disentangling-shared-and-private-information","Disentangling Shared and Private Information",[22,6564,6565],{},"Multimodal sentiment analysis often suffers from data incompleteness, where one or more modalities (e.g., audio, video, or text) are missing during inference. The MIDAS (Mutual Information Disentanglement with Uncertainty-Aware Fusion) framework addresses this by separating multimodal representations into two distinct components: shared information, which is common across modalities, and private information, which is unique to a specific modality. By disentangling these features, the model ensures that the shared representation remains robust even if specific modalities are absent, as the shared core captures the underlying sentiment signal that persists across different data streams.",[17,6567,6569],{"id":6568},"uncertainty-aware-fusion-for-robust-prediction","Uncertainty-Aware Fusion for Robust Prediction",[22,6571,6572],{},"Beyond disentanglement, MIDAS employs an uncertainty-aware fusion mechanism to handle the noise and variability inherent in incomplete data. When modalities are missing or degraded, the model estimates the uncertainty associated with each available feature. Instead of treating all inputs with equal weight, the fusion process dynamically adjusts based on the confidence level of the available modalities. This prevents the model from relying on unreliable or incomplete data streams, effectively mitigating the performance drop typically seen in multimodal systems when input data is sparse. By integrating these uncertainty estimates, MIDAS maintains high predictive accuracy across varying degrees of modality absence, proving more resilient than traditional fusion techniques that assume complete input availability.",{"title":40,"searchDepth":41,"depth":41,"links":6574},[6575,6576],{"id":6561,"depth":41,"text":6562},{"id":6568,"depth":41,"text":6569},[47],{"content_references":6579,"triage":6583},[6580],{"type":54,"title":6581,"url":6582,"context":57},"MIDAS: Mutual Information Disentanglement with Uncertainty-Aware Fusion for Incomplete Multimodal Sentiment Analysis","https:\u002F\u002Farxiv.org\u002Fabs\u002F2608.09986",{"relevance":60,"novelty":59,"quality":59,"actionability":41,"composite":6584,"reasoning":6585},3.25,"Category: AI & LLMs. The article discusses a novel framework for handling incomplete multimodal data, which is relevant to AI engineering and machine learning. However, while it presents new insights into the MIDAS framework, it lacks practical applications or specific techniques that the audience can directly implement.","\u002Fsummaries\u002F11f943a4cc8b55bd-midas-handling-incomplete-multimodal-sentiment-ana-summary","2026-08-13 03:25:41",{"title":6551,"description":40},{"loc":6586},"11f943a4cc8b55bd","summaries\u002F11f943a4cc8b55bd-midas-handling-incomplete-multimodal-sentiment-ana-summary",[74,6593,75],"research","The MIDAS framework addresses incomplete multimodal data by disentangling shared and private information while using uncertainty-aware fusion to maintain sentiment prediction accuracy when modalities are missing.",[75],"NsGat21NKVM59FEcwj3hv3veMTKA8FWug4GMpp0Zz38",{"id":6598,"title":6599,"ai":6600,"body":6605,"categories":6633,"created_at":48,"date_modified":48,"description":40,"extension":49,"faq":48,"featured":50,"kicker_label":48,"meta":6634,"navigation":63,"path":6642,"published_at":6643,"question":48,"scraped_at":6643,"seo":6644,"sitemap":6645,"source_id":6646,"source_name":69,"source_type":70,"source_url":6638,"stem":6647,"tags":6648,"thumbnail_url":48,"tldr":6649,"tweet":48,"unknown_tags":6650,"__hash__":6651},"summaries\u002Fsummaries\u002Fa7684c8b0b109425-moving-beyond-single-vector-graph-representations-summary.md","Moving Beyond Single-Vector Graph Representations",{"provider":7,"model":8,"input_tokens":6601,"output_tokens":6602,"processing_time_ms":6603,"cost_usd":6604},4001,487,2637,0.00173075,{"type":14,"value":6606,"toc":6628},[6607,6611,6614,6618,6621,6625],[17,6608,6610],{"id":6609},"the-limitation-of-single-vector-embeddings","The Limitation of Single-Vector Embeddings",[22,6612,6613],{},"Traditional graph representation learning often relies on mapping an entire graph structure into a single, fixed-length vector. While effective for simple classification tasks, this approach struggles with the inherent complexity of real-world graphs, which often contain multiple, overlapping semantic labels or properties. A single vector acts as a bottleneck, forcing the model to compress diverse structural and functional information into a lossy representation that fails to distinguish between distinct graph features.",[17,6615,6617],{"id":6616},"multi-semantic-basis-learning-as-a-solution","Multi-Semantic Basis Learning as a Solution",[22,6619,6620],{},"The authors propose a transition toward Multi-Semantic Basis Learning. Instead of forcing a graph into one vector, the model learns a set of basis vectors, each corresponding to a specific semantic dimension or label. This allows the foundation model to represent a graph as a combination of these bases, providing a more granular and interpretable output. By decoupling the representation into multiple semantic components, the model can better handle multi-label scenarios where a single graph might simultaneously belong to several categories or exhibit different functional roles.",[17,6622,6624],{"id":6623},"implications-for-graph-foundation-models","Implications for Graph Foundation Models",[22,6626,6627],{},"This shift is critical for the development of true Graph Foundation Models (GFMs). By adopting a multi-semantic approach, GFMs can achieve better generalization across diverse downstream tasks without needing extensive fine-tuning for every specific label. This architecture mirrors the success of multi-head attention mechanisms in Transformers, where different heads attend to different aspects of the input data, suggesting that graph models must evolve to treat graph semantics as a multi-faceted rather than monolithic entity.",{"title":40,"searchDepth":41,"depth":41,"links":6629},[6630,6631,6632],{"id":6609,"depth":41,"text":6610},{"id":6616,"depth":41,"text":6617},{"id":6623,"depth":41,"text":6624},[47],{"content_references":6635,"triage":6640},[6636],{"type":54,"title":6637,"url":6638,"context":6639},"Towards Multi-Label Graph Foundation Models: from Single-Vector Representation Learning to Multi-Semantic Basis Learning","https:\u002F\u002Farxiv.org\u002Fabs\u002F2608.06394","reviewed",{"relevance":60,"novelty":59,"quality":59,"actionability":41,"composite":6584,"reasoning":6641},"Category: AI & LLMs. The article discusses a novel approach to graph representation learning, addressing a limitation in current models, which is relevant to AI and LLMs. However, it lacks practical applications or frameworks that the audience can directly implement, making it less actionable.","\u002Fsummaries\u002Fa7684c8b0b109425-moving-beyond-single-vector-graph-representations-summary","2026-08-11 03:21:33",{"title":6599,"description":40},{"loc":6642},"a7684c8b0b109425","summaries\u002Fa7684c8b0b109425-moving-beyond-single-vector-graph-representations-summary",[74,6593,75],"The paper proposes shifting from single-vector graph embeddings to multi-semantic basis learning to better capture the complex, multi-label nature of graph data in foundation models.",[75],"u0bIr558WSyDQ2txSys9yceQauB-EoH2BITrVAdBadw",{"id":6653,"title":6654,"ai":6655,"body":6660,"categories":6706,"created_at":48,"date_modified":48,"description":40,"extension":49,"faq":48,"featured":50,"kicker_label":48,"meta":6707,"navigation":63,"path":6715,"published_at":6716,"question":48,"scraped_at":6716,"seo":6717,"sitemap":6718,"source_id":6719,"source_name":69,"source_type":70,"source_url":6712,"stem":6720,"tags":6721,"thumbnail_url":48,"tldr":6722,"tweet":48,"unknown_tags":6723,"__hash__":6724},"summaries\u002Fsummaries\u002Fde28cb4564806b5e-crowdmath-a-new-dataset-for-mathematical-research-summary.md","CrowdMath: A New Dataset for Mathematical Research Reasoning",{"provider":7,"model":8,"input_tokens":6656,"output_tokens":6657,"processing_time_ms":6658,"cost_usd":6659},4086,485,2819,0.001749,{"type":14,"value":6661,"toc":6702},[6662,6666,6669,6673,6676,6699],[17,6663,6665],{"id":6664},"bridging-the-gap-in-mathematical-reasoning","Bridging the Gap in Mathematical Reasoning",[22,6667,6668],{},"CrowdMath addresses a critical bottleneck in training Large Language Models (LLMs): the scarcity of high-quality, multi-step mathematical reasoning data that reflects actual research-level discourse. While many existing datasets focus on competition-style problems or textbook exercises, CrowdMath captures the nuance of collaborative mathematical problem-solving, providing a more robust foundation for training models to handle complex, open-ended research inquiries.",[17,6670,6672],{"id":6671},"dataset-composition-and-utility","Dataset Composition and Utility",[22,6674,6675],{},"The dataset is constructed from crowdsourced discussions, offering a unique look at how mathematicians iterate, verify, and refine their arguments. By leveraging these real-world interactions, CrowdMath provides:",[6677,6678,6679,6687,6693],"ul",{},[6680,6681,6682,6686],"li",{},[6683,6684,6685],"strong",{},"Multi-turn Reasoning:"," Unlike static problem-answer pairs, the dataset includes the conversational flow of mathematical discovery, which is essential for training models to perform chain-of-thought reasoning more effectively.",[6680,6688,6689,6692],{},[6683,6690,6691],{},"Research-Level Complexity:"," The content moves beyond standard curriculum mathematics, pushing models to engage with the ambiguity and depth found in professional research environments.",[6680,6694,6695,6698],{},[6683,6696,6697],{},"Evaluation Benchmarks:"," The dataset serves as a rigorous testbed for evaluating an AI's ability to maintain logical consistency over long, complex derivations and to participate in collaborative verification processes.",[22,6700,6701],{},"By providing this data, the authors aim to move the field toward models that can act as genuine research assistants rather than just solvers of well-defined, closed-form problems.",{"title":40,"searchDepth":41,"depth":41,"links":6703},[6704,6705],{"id":6664,"depth":41,"text":6665},{"id":6671,"depth":41,"text":6672},[47],{"content_references":6708,"triage":6713},[6709],{"type":54,"title":6710,"author":6711,"url":6712,"context":57},"CrowdMath: A Dataset of Crowdsourced Mathematical Research Discussions","Unknown","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.06526",{"relevance":60,"novelty":59,"quality":59,"actionability":41,"composite":6584,"reasoning":6714},"Category: AI & LLMs. The article discusses a new dataset aimed at improving AI reasoning capabilities, which aligns with the AI & LLMs category. While it presents novel insights into the dataset's construction and potential applications, it lacks specific actionable steps for the audience to implement in their own projects.","\u002Fsummaries\u002Fde28cb4564806b5e-crowdmath-a-new-dataset-for-mathematical-research-summary","2026-06-08 12:56:51",{"title":6654,"description":40},{"loc":6715},"de28cb4564806b5e","summaries\u002Fde28cb4564806b5e-crowdmath-a-new-dataset-for-mathematical-research-summary",[74,6593,75],"CrowdMath is a new dataset derived from crowdsourced mathematical research discussions, designed to improve AI reasoning capabilities in complex, multi-step mathematical domains.",[75],"XLKX1WhZKB_8AqFWyn5Z3mvdz5Tuh_onQ7MVoXwU23g"]