Add GitHub ML run 20260928T183308000000Z-7c10a585
Browse files
.gitattributes
CHANGED
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@@ -81,3 +81,4 @@ data/observations/2026/09/27/20260927T150859000000Z-f5fb8d48.jsonl filter=lfs di
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data/observations/2026/09/27/20260927T155349000000Z-fbebcc43.jsonl filter=lfs diff=lfs merge=lfs -text
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data/observations/2026/09/27/20260927T160959000000Z-2c2fd226.jsonl filter=lfs diff=lfs merge=lfs -text
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data/observations/2026/09/28/20260928T174651000000Z-778c6d7c.jsonl filter=lfs diff=lfs merge=lfs -text
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data/observations/2026/09/27/20260927T155349000000Z-fbebcc43.jsonl filter=lfs diff=lfs merge=lfs -text
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data/observations/2026/09/27/20260927T160959000000Z-2c2fd226.jsonl filter=lfs diff=lfs merge=lfs -text
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data/observations/2026/09/28/20260928T174651000000Z-778c6d7c.jsonl filter=lfs diff=lfs merge=lfs -text
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data/observations/2026/09/28/20260928T183308000000Z-7c10a585.jsonl filter=lfs diff=lfs merge=lfs -text
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coverage/20260928T183308000000Z-7c10a585.json
ADDED
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@@ -0,0 +1,2812 @@
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data/observations/2026/09/28/20260928T183308000000Z-7c10a585.jsonl
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state/historical-sample.json
CHANGED
|
@@ -2401,67 +2401,78 @@
|
|
| 2401 |
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|
| 2402 |
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| 2403 |
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| 2404 |
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| 2405 |
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|
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|
| 2408 |
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| 2410 |
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2026
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| 2411 |
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|
| 2412 |
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|
| 2413 |
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|
| 2414 |
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|
| 2415 |
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| 2416 |
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|
|
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|
| 2417 |
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|
| 2418 |
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|
| 2419 |
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|
| 2420 |
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| 2421 |
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| 2422 |
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|
| 2423 |
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|
| 2424 |
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|
| 2425 |
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|
| 2426 |
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|
| 2427 |
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| 2428 |
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2026
|
|
|
|
| 2429 |
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|
| 2430 |
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|
| 2431 |
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|
| 2432 |
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|
| 2433 |
"years": [
|
| 2434 |
-
2026
|
|
|
|
| 2435 |
]
|
| 2436 |
},
|
| 2437 |
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|
| 2438 |
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|
| 2439 |
"years": [
|
| 2440 |
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2026
|
|
|
|
| 2441 |
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|
| 2442 |
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|
| 2443 |
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|
| 2444 |
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|
| 2445 |
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|
| 2446 |
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2026
|
|
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|
| 2447 |
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|
| 2448 |
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|
| 2449 |
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|
| 2450 |
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|
| 2451 |
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| 2452 |
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|
|
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|
| 2453 |
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|
| 2454 |
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|
| 2455 |
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|
| 2456 |
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|
| 2457 |
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|
| 2458 |
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2026
|
|
|
|
| 2459 |
]
|
| 2460 |
},
|
| 2461 |
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|
| 2462 |
"query": "\"intrusion detection\" \"machine learning\" in:description,readme",
|
| 2463 |
"years": [
|
| 2464 |
-
2026
|
|
|
|
| 2465 |
]
|
| 2466 |
},
|
| 2467 |
"applied.inventory-optimization": {
|
|
@@ -2814,67 +2825,78 @@
|
|
| 2814 |
"bio.metagenomics": {
|
| 2815 |
"query": "\"metagenomic classification\" in:description,readme",
|
| 2816 |
"years": [
|
| 2817 |
-
2026
|
|
|
|
| 2818 |
]
|
| 2819 |
},
|
| 2820 |
"bio.microbiome": {
|
| 2821 |
"query": "\"microbiome\" \"machine learning\" in:description,readme",
|
| 2822 |
"years": [
|
| 2823 |
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2026
|
|
|
|
| 2824 |
]
|
| 2825 |
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|
| 2826 |
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|
| 2827 |
"query": "\"cell segmentation\" microscopy in:description,readme",
|
| 2828 |
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|
| 2829 |
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2026
|
|
|
|
| 2830 |
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|
| 2831 |
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|
| 2832 |
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|
| 2833 |
"query": "\"molecular dynamics\" in:description",
|
| 2834 |
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|
| 2835 |
-
2026
|
|
|
|
| 2836 |
]
|
| 2837 |
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|
| 2838 |
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|
| 2839 |
"query": "\"machine learning force field\" in:readme",
|
| 2840 |
"years": [
|
| 2841 |
-
2026
|
|
|
|
| 2842 |
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|
| 2843 |
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|
| 2844 |
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|
| 2845 |
"query": "\"phylogenetics\" in:description",
|
| 2846 |
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|
| 2847 |
-
2026
|
|
|
|
| 2848 |
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|
| 2849 |
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|
| 2850 |
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|
| 2851 |
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|
| 2852 |
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| 2853 |
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2026
|
|
|
|
| 2854 |
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|
| 2855 |
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|
| 2856 |
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|
| 2857 |
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|
| 2858 |
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|
| 2859 |
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2026
|
|
|
|
| 2860 |
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|
| 2861 |
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|
| 2862 |
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|
| 2863 |
"query": "\"protein-protein interaction prediction\" in:readme",
|
| 2864 |
"years": [
|
| 2865 |
-
2026
|
|
|
|
| 2866 |
]
|
| 2867 |
},
|
| 2868 |
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|
| 2869 |
"query": "\"protein structure prediction\" in:description",
|
| 2870 |
"years": [
|
| 2871 |
-
2026
|
|
|
|
| 2872 |
]
|
| 2873 |
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|
| 2874 |
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|
| 2875 |
"query": "enhancer prediction genomics in:description,readme",
|
| 2876 |
"years": [
|
| 2877 |
-
2026
|
|
|
|
| 2878 |
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|
| 2879 |
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|
| 2880 |
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|
|
@@ -3118,67 +3140,78 @@
|
|
| 3118 |
"efficiency.gpu-kernels": {
|
| 3119 |
"query": "\"GPU kernel\" in:description",
|
| 3120 |
"years": [
|
| 3121 |
-
2026
|
|
|
|
| 3122 |
]
|
| 3123 |
},
|
| 3124 |
"efficiency.gradient-optimization": {
|
| 3125 |
"query": "\"gradient-based optimization\" in:description",
|
| 3126 |
"years": [
|
| 3127 |
-
2026
|
|
|
|
| 3128 |
]
|
| 3129 |
},
|
| 3130 |
"efficiency.hyperparameter-optimization": {
|
| 3131 |
"query": "\"hyperparameter optimization\" in:description",
|
| 3132 |
"years": [
|
| 3133 |
-
2026
|
|
|
|
| 3134 |
]
|
| 3135 |
},
|
| 3136 |
"efficiency.inference-systems": {
|
| 3137 |
"query": "\"inference engine\" \"machine learning\" in:description,readme",
|
| 3138 |
"years": [
|
| 3139 |
-
2026
|
|
|
|
| 3140 |
]
|
| 3141 |
},
|
| 3142 |
"efficiency.knowledge-distillation": {
|
| 3143 |
"query": "\"knowledge distillation\" in:description",
|
| 3144 |
"years": [
|
| 3145 |
-
2026
|
|
|
|
| 3146 |
]
|
| 3147 |
},
|
| 3148 |
"efficiency.kv-cache": {
|
| 3149 |
"query": "\"KV cache\" in:description",
|
| 3150 |
"years": [
|
| 3151 |
-
2026
|
|
|
|
| 3152 |
]
|
| 3153 |
},
|
| 3154 |
"efficiency.lora": {
|
| 3155 |
"query": "LoRA in:description",
|
| 3156 |
"years": [
|
| 3157 |
-
2026
|
|
|
|
| 3158 |
]
|
| 3159 |
},
|
| 3160 |
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|
| 3161 |
"query": "\"low-rank factorization\" in:description",
|
| 3162 |
"years": [
|
| 3163 |
-
2026
|
|
|
|
| 3164 |
]
|
| 3165 |
},
|
| 3166 |
"efficiency.mixed-precision-training": {
|
| 3167 |
"query": "\"mixed precision training\" in:description",
|
| 3168 |
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|
| 3169 |
-
2026
|
|
|
|
| 3170 |
]
|
| 3171 |
},
|
| 3172 |
"efficiency.mixture-of-experts": {
|
| 3173 |
"query": "\"mixture of experts\" in:description",
|
| 3174 |
"years": [
|
| 3175 |
-
2026
|
|
|
|
| 3176 |
]
|
| 3177 |
},
|
| 3178 |
"efficiency.model-compression": {
|
| 3179 |
"query": "\"model compression\" in:description",
|
| 3180 |
"years": [
|
| 3181 |
-
2026
|
|
|
|
| 3182 |
]
|
| 3183 |
},
|
| 3184 |
"efficiency.neural-architecture-search": {
|
|
@@ -3294,67 +3327,78 @@
|
|
| 3294 |
"gap2026.econometrics-double-ml": {
|
| 3295 |
"query": "\"double machine learning\" econometrics in:description,readme",
|
| 3296 |
"years": [
|
| 3297 |
-
2026
|
|
|
|
| 3298 |
]
|
| 3299 |
},
|
| 3300 |
"gap2026.econometrics-heterogeneous-effects": {
|
| 3301 |
"query": "\"heterogeneous treatment effects\" machine learning economics in:description,readme",
|
| 3302 |
"years": [
|
| 3303 |
-
2026
|
|
|
|
| 3304 |
]
|
| 3305 |
},
|
| 3306 |
"gap2026.econometrics-policy-learning": {
|
| 3307 |
"query": "\"policy learning\" causal machine learning economics in:description,readme",
|
| 3308 |
"years": [
|
| 3309 |
-
2026
|
|
|
|
| 3310 |
]
|
| 3311 |
},
|
| 3312 |
"gap2026.forecasting-count-data": {
|
| 3313 |
"query": "\"count time series forecasting\" neural in:description,readme",
|
| 3314 |
"years": [
|
| 3315 |
-
2026
|
|
|
|
| 3316 |
]
|
| 3317 |
},
|
| 3318 |
"gap2026.forecasting-hierarchical": {
|
| 3319 |
"query": "\"hierarchical time series forecasting\" machine learning in:description,readme",
|
| 3320 |
"years": [
|
| 3321 |
-
2026
|
|
|
|
| 3322 |
]
|
| 3323 |
},
|
| 3324 |
"gap2026.forecasting-intermittent-demand": {
|
| 3325 |
"query": "\"intermittent demand forecasting\" machine learning in:description,readme",
|
| 3326 |
"years": [
|
| 3327 |
-
2026
|
|
|
|
| 3328 |
]
|
| 3329 |
},
|
| 3330 |
"gap2026.forecasting-quantile": {
|
| 3331 |
"query": "\"neural quantile forecasting\" in:description,readme",
|
| 3332 |
"years": [
|
| 3333 |
-
2026
|
|
|
|
| 3334 |
]
|
| 3335 |
},
|
| 3336 |
"gap2026.green-ai-carbon": {
|
| 3337 |
"query": "\"carbon emissions\" machine learning training in:description,readme",
|
| 3338 |
"years": [
|
| 3339 |
-
2026
|
|
|
|
| 3340 |
]
|
| 3341 |
},
|
| 3342 |
"gap2026.green-ai-carbon-aware-scheduling": {
|
| 3343 |
"query": "\"carbon-aware\" machine learning scheduling in:description,readme",
|
| 3344 |
"years": [
|
| 3345 |
-
2026
|
|
|
|
| 3346 |
]
|
| 3347 |
},
|
| 3348 |
"gap2026.green-ai-efficient-inference": {
|
| 3349 |
"query": "\"energy efficient inference\" neural network in:description,readme",
|
| 3350 |
"years": [
|
| 3351 |
-
2026
|
|
|
|
| 3352 |
]
|
| 3353 |
},
|
| 3354 |
"gap2026.green-ai-energy": {
|
| 3355 |
"query": "\"energy efficient machine learning\" in:description,readme",
|
| 3356 |
"years": [
|
| 3357 |
-
2026
|
|
|
|
| 3358 |
]
|
| 3359 |
},
|
| 3360 |
"gap2026.math-learned-optimization": {
|
|
@@ -3476,67 +3520,78 @@
|
|
| 3476 |
"general.contrastive-learning": {
|
| 3477 |
"query": "\"contrastive learning\" in:description,readme",
|
| 3478 |
"years": [
|
| 3479 |
-
2026
|
|
|
|
| 3480 |
]
|
| 3481 |
},
|
| 3482 |
"general.decision-trees": {
|
| 3483 |
"query": "\"decision tree\" \"machine learning\" in:description,readme",
|
| 3484 |
"years": [
|
| 3485 |
-
2026
|
|
|
|
| 3486 |
]
|
| 3487 |
},
|
| 3488 |
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|
| 3489 |
"query": "\"deep learning\" in:description",
|
| 3490 |
"years": [
|
| 3491 |
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2026
|
|
|
|
| 3492 |
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|
| 3493 |
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|
| 3494 |
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|
| 3495 |
"query": "\"deep learning\" in:readme",
|
| 3496 |
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|
| 3497 |
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2026
|
|
|
|
| 3498 |
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|
| 3499 |
},
|
| 3500 |
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|
| 3501 |
"query": "\"dimensionality reduction\" in:description,readme",
|
| 3502 |
"years": [
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| 3503 |
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2026
|
|
|
|
| 3504 |
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|
| 3505 |
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|
| 3506 |
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|
| 3507 |
"query": "\"domain adaptation\" \"machine learning\" in:description,readme",
|
| 3508 |
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|
| 3509 |
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2026
|
|
|
|
| 3510 |
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|
| 3511 |
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|
| 3512 |
"general.gaussian-mixture-models": {
|
| 3513 |
"query": "\"Gaussian mixture model\" in:description,readme",
|
| 3514 |
"years": [
|
| 3515 |
-
2026
|
|
|
|
| 3516 |
]
|
| 3517 |
},
|
| 3518 |
"general.gaussian-process": {
|
| 3519 |
"query": "\"Gaussian process\" in:description",
|
| 3520 |
"years": [
|
| 3521 |
-
2026
|
|
|
|
| 3522 |
]
|
| 3523 |
},
|
| 3524 |
"general.gradient-boosting": {
|
| 3525 |
"query": "\"gradient boosting\" in:description",
|
| 3526 |
"years": [
|
| 3527 |
-
2026
|
|
|
|
| 3528 |
]
|
| 3529 |
},
|
| 3530 |
"general.hidden-markov-models": {
|
| 3531 |
"query": "\"hidden Markov model\" \"machine learning\" in:description,readme",
|
| 3532 |
"years": [
|
| 3533 |
-
2026
|
|
|
|
| 3534 |
]
|
| 3535 |
},
|
| 3536 |
"general.logistic-regression": {
|
| 3537 |
"query": "\"logistic regression\" in:description,readme",
|
| 3538 |
"years": [
|
| 3539 |
-
2026
|
|
|
|
| 3540 |
]
|
| 3541 |
},
|
| 3542 |
"general.machine-learning-description": {
|
|
@@ -3748,67 +3803,78 @@
|
|
| 3748 |
"geo.geospatial-foundation-models": {
|
| 3749 |
"query": "\"geospatial foundation model\" in:readme",
|
| 3750 |
"years": [
|
| 3751 |
-
2026
|
|
|
|
| 3752 |
]
|
| 3753 |
},
|
| 3754 |
"geo.geospatial-knowledge-graph": {
|
| 3755 |
"query": "\"geospatial knowledge graph\" in:description,readme",
|
| 3756 |
"years": [
|
| 3757 |
-
2026
|
|
|
|
| 3758 |
]
|
| 3759 |
},
|
| 3760 |
"geo.hydrology": {
|
| 3761 |
"query": "\"hydrology machine learning\" in:readme",
|
| 3762 |
"years": [
|
| 3763 |
-
2026
|
|
|
|
| 3764 |
]
|
| 3765 |
},
|
| 3766 |
"geo.land-cover": {
|
| 3767 |
"query": "\"land cover\" in:readme",
|
| 3768 |
"years": [
|
| 3769 |
-
2026
|
|
|
|
| 3770 |
]
|
| 3771 |
},
|
| 3772 |
"geo.land-use": {
|
| 3773 |
"query": "\"land use\" in:readme",
|
| 3774 |
"years": [
|
| 3775 |
-
2026
|
|
|
|
| 3776 |
]
|
| 3777 |
},
|
| 3778 |
"geo.lidar": {
|
| 3779 |
"query": "LiDAR in:description \"deep learning\"",
|
| 3780 |
"years": [
|
| 3781 |
-
2026
|
|
|
|
| 3782 |
]
|
| 3783 |
},
|
| 3784 |
"geo.mobility-modeling": {
|
| 3785 |
"query": "\"human mobility\" \"machine learning\" in:description,readme",
|
| 3786 |
"years": [
|
| 3787 |
-
2026
|
|
|
|
| 3788 |
]
|
| 3789 |
},
|
| 3790 |
"geo.object-detection": {
|
| 3791 |
"query": "\"object detection\" \"remote sensing\" in:description,readme",
|
| 3792 |
"years": [
|
| 3793 |
-
2026
|
|
|
|
| 3794 |
]
|
| 3795 |
},
|
| 3796 |
"geo.ocean-remote-sensing": {
|
| 3797 |
"query": "\"ocean remote sensing\" in:description,readme",
|
| 3798 |
"years": [
|
| 3799 |
-
2026
|
|
|
|
| 3800 |
]
|
| 3801 |
},
|
| 3802 |
"geo.precipitation-forecasting": {
|
| 3803 |
"query": "\"precipitation forecasting\" in:description,readme",
|
| 3804 |
"years": [
|
| 3805 |
-
2026
|
|
|
|
| 3806 |
]
|
| 3807 |
},
|
| 3808 |
"geo.sar-imagery": {
|
| 3809 |
"query": "\"synthetic aperture radar\" in:readme",
|
| 3810 |
"years": [
|
| 3811 |
-
2026
|
|
|
|
| 3812 |
]
|
| 3813 |
},
|
| 3814 |
"geo.satellite-imagery": {
|
|
@@ -3918,67 +3984,78 @@
|
|
| 3918 |
"graph.graph-foundation-model": {
|
| 3919 |
"query": "\"graph foundation model\" in:description",
|
| 3920 |
"years": [
|
| 3921 |
-
2026
|
|
|
|
| 3922 |
]
|
| 3923 |
},
|
| 3924 |
"graph.graph-generation": {
|
| 3925 |
"query": "\"graph generation\" in:readme",
|
| 3926 |
"years": [
|
| 3927 |
-
2026
|
|
|
|
| 3928 |
]
|
| 3929 |
},
|
| 3930 |
"graph.graph-transformer": {
|
| 3931 |
"query": "\"graph transformer\" in:description",
|
| 3932 |
"years": [
|
| 3933 |
-
2026
|
|
|
|
| 3934 |
]
|
| 3935 |
},
|
| 3936 |
"graph.hypergraph-neural-network": {
|
| 3937 |
"query": "\"hypergraph neural network\" in:description",
|
| 3938 |
"years": [
|
| 3939 |
-
2026
|
|
|
|
| 3940 |
]
|
| 3941 |
},
|
| 3942 |
"graph.knowledge-graph-embedding": {
|
| 3943 |
"query": "\"knowledge graph embedding\" in:description",
|
| 3944 |
"years": [
|
| 3945 |
-
2026
|
|
|
|
| 3946 |
]
|
| 3947 |
},
|
| 3948 |
"graph.knowledge-graphs": {
|
| 3949 |
"query": "topic:knowledge-graph",
|
| 3950 |
"years": [
|
| 3951 |
-
2026
|
|
|
|
| 3952 |
]
|
| 3953 |
},
|
| 3954 |
"graph.link-prediction": {
|
| 3955 |
"query": "\"link prediction\" in:description",
|
| 3956 |
"years": [
|
| 3957 |
-
2026
|
|
|
|
| 3958 |
]
|
| 3959 |
},
|
| 3960 |
"graph.manifold-learning": {
|
| 3961 |
"query": "\"manifold learning\" in:description",
|
| 3962 |
"years": [
|
| 3963 |
-
2026
|
|
|
|
| 3964 |
]
|
| 3965 |
},
|
| 3966 |
"graph.mesh-graph-learning": {
|
| 3967 |
"query": "\"mesh graph neural network\" in:description",
|
| 3968 |
"years": [
|
| 3969 |
-
2026
|
|
|
|
| 3970 |
]
|
| 3971 |
},
|
| 3972 |
"graph.molecular-graphs": {
|
| 3973 |
"query": "\"molecular graph neural network\" in:readme",
|
| 3974 |
"years": [
|
| 3975 |
-
2026
|
|
|
|
| 3976 |
]
|
| 3977 |
},
|
| 3978 |
"graph.neural-ode-graph": {
|
| 3979 |
"query": "\"graph neural ODE\" in:description",
|
| 3980 |
"years": [
|
| 3981 |
-
2026
|
|
|
|
| 3982 |
]
|
| 3983 |
},
|
| 3984 |
"graph.persistent-homology": {
|
|
@@ -4116,67 +4193,78 @@
|
|
| 4116 |
"llm.generative-ai": {
|
| 4117 |
"query": "\"generative AI\" in:description",
|
| 4118 |
"years": [
|
| 4119 |
-
2026
|
|
|
|
| 4120 |
]
|
| 4121 |
},
|
| 4122 |
"llm.instruction-tuning": {
|
| 4123 |
"query": "\"instruction tuning\" in:readme",
|
| 4124 |
"years": [
|
| 4125 |
-
2026
|
|
|
|
| 4126 |
]
|
| 4127 |
},
|
| 4128 |
"llm.language-model": {
|
| 4129 |
"query": "\"language model\" in:description",
|
| 4130 |
"years": [
|
| 4131 |
-
2026
|
|
|
|
| 4132 |
]
|
| 4133 |
},
|
| 4134 |
"llm.language-models": {
|
| 4135 |
"query": "topic:large-language-models",
|
| 4136 |
"years": [
|
| 4137 |
-
2026
|
|
|
|
| 4138 |
]
|
| 4139 |
},
|
| 4140 |
"llm.large-language-model": {
|
| 4141 |
"query": "\"large language model\" in:description",
|
| 4142 |
"years": [
|
| 4143 |
-
2026
|
|
|
|
| 4144 |
]
|
| 4145 |
},
|
| 4146 |
"llm.long-context": {
|
| 4147 |
"query": "\"long context\" \"language model\" in:readme",
|
| 4148 |
"years": [
|
| 4149 |
-
2026
|
|
|
|
| 4150 |
]
|
| 4151 |
},
|
| 4152 |
"llm.multimodal": {
|
| 4153 |
"query": "\"multimodal language model\" in:description",
|
| 4154 |
"years": [
|
| 4155 |
-
2026
|
|
|
|
| 4156 |
]
|
| 4157 |
},
|
| 4158 |
"llm.parameter-efficient-finetuning": {
|
| 4159 |
"query": "\"parameter-efficient fine-tuning\" in:readme",
|
| 4160 |
"years": [
|
| 4161 |
-
2026
|
|
|
|
| 4162 |
]
|
| 4163 |
},
|
| 4164 |
"llm.preference-optimization": {
|
| 4165 |
"query": "\"direct preference optimization\" in:readme",
|
| 4166 |
"years": [
|
| 4167 |
-
2026
|
|
|
|
| 4168 |
]
|
| 4169 |
},
|
| 4170 |
"llm.quantization": {
|
| 4171 |
"query": "\"LLM quantization\" in:readme",
|
| 4172 |
"years": [
|
| 4173 |
-
2026
|
|
|
|
| 4174 |
]
|
| 4175 |
},
|
| 4176 |
"llm.speculative-decoding": {
|
| 4177 |
"query": "\"speculative decoding\" in:readme",
|
| 4178 |
"years": [
|
| 4179 |
-
2026
|
|
|
|
| 4180 |
]
|
| 4181 |
},
|
| 4182 |
"llm.synthetic-data": {
|
|
@@ -4311,67 +4399,78 @@
|
|
| 4311 |
"medical.eeg": {
|
| 4312 |
"query": "EEG \"deep learning\" in:description,readme",
|
| 4313 |
"years": [
|
| 4314 |
-
2026
|
|
|
|
| 4315 |
]
|
| 4316 |
},
|
| 4317 |
"medical.ehr": {
|
| 4318 |
"query": "\"electronic health record\" in:readme",
|
| 4319 |
"years": [
|
| 4320 |
-
2026
|
|
|
|
| 4321 |
]
|
| 4322 |
},
|
| 4323 |
"medical.genomics": {
|
| 4324 |
"query": "\"clinical genomics\" in:description,readme",
|
| 4325 |
"years": [
|
| 4326 |
-
2026
|
|
|
|
| 4327 |
]
|
| 4328 |
},
|
| 4329 |
"medical.histopathology": {
|
| 4330 |
"query": "\"histopathology image analysis\" in:readme",
|
| 4331 |
"years": [
|
| 4332 |
-
2026
|
|
|
|
| 4333 |
]
|
| 4334 |
},
|
| 4335 |
"medical.medical-image-reconstruction": {
|
| 4336 |
"query": "\"MRI reconstruction\" in:description,readme",
|
| 4337 |
"years": [
|
| 4338 |
-
2026
|
|
|
|
| 4339 |
]
|
| 4340 |
},
|
| 4341 |
"medical.medical-image-registration": {
|
| 4342 |
"query": "\"medical image registration\" in:description,readme",
|
| 4343 |
"years": [
|
| 4344 |
-
2026
|
|
|
|
| 4345 |
]
|
| 4346 |
},
|
| 4347 |
"medical.medical-image-segmentation": {
|
| 4348 |
"query": "\"medical image segmentation\" in:description",
|
| 4349 |
"years": [
|
| 4350 |
-
2026
|
|
|
|
| 4351 |
]
|
| 4352 |
},
|
| 4353 |
"medical.medical-imaging": {
|
| 4354 |
"query": "\"medical imaging\" in:readme",
|
| 4355 |
"years": [
|
| 4356 |
-
2026
|
|
|
|
| 4357 |
]
|
| 4358 |
},
|
| 4359 |
"medical.medical-language-model": {
|
| 4360 |
"query": "\"medical language model\" in:description",
|
| 4361 |
"years": [
|
| 4362 |
-
2026
|
|
|
|
| 4363 |
]
|
| 4364 |
},
|
| 4365 |
"medical.medical-robotics": {
|
| 4366 |
"query": "\"surgical robotics\" \"machine learning\" in:description,readme",
|
| 4367 |
"years": [
|
| 4368 |
-
2026
|
|
|
|
| 4369 |
]
|
| 4370 |
},
|
| 4371 |
"medical.neural-decoding": {
|
| 4372 |
"query": "\"neural data decoding\" in:description",
|
| 4373 |
"years": [
|
| 4374 |
-
2026
|
|
|
|
| 4375 |
]
|
| 4376 |
},
|
| 4377 |
"medical.neuroimaging": {
|
|
@@ -4481,67 +4580,78 @@
|
|
| 4481 |
"multimodal.image-to-3d": {
|
| 4482 |
"query": "\"image to 3D\" in:readme",
|
| 4483 |
"years": [
|
| 4484 |
-
2026
|
|
|
|
| 4485 |
]
|
| 4486 |
},
|
| 4487 |
"multimodal.image-to-video": {
|
| 4488 |
"query": "\"image to video\" in:readme",
|
| 4489 |
"years": [
|
| 4490 |
-
2026
|
|
|
|
| 4491 |
]
|
| 4492 |
},
|
| 4493 |
"multimodal.motion-generation": {
|
| 4494 |
"query": "\"human motion generation\" in:readme",
|
| 4495 |
"years": [
|
| 4496 |
-
2026
|
|
|
|
| 4497 |
]
|
| 4498 |
},
|
| 4499 |
"multimodal.nerf": {
|
| 4500 |
"query": "topic:nerf",
|
| 4501 |
"years": [
|
| 4502 |
-
2026
|
|
|
|
| 4503 |
]
|
| 4504 |
},
|
| 4505 |
"multimodal.neural-rendering": {
|
| 4506 |
"query": "\"neural rendering\" \"radiance fields\" in:description",
|
| 4507 |
"years": [
|
| 4508 |
-
2026
|
|
|
|
| 4509 |
]
|
| 4510 |
},
|
| 4511 |
"multimodal.point-cloud": {
|
| 4512 |
"query": "\"point cloud\" in:description",
|
| 4513 |
"years": [
|
| 4514 |
-
2026
|
|
|
|
| 4515 |
]
|
| 4516 |
},
|
| 4517 |
"multimodal.scene-understanding": {
|
| 4518 |
"query": "\"scene understanding\" in:description",
|
| 4519 |
"years": [
|
| 4520 |
-
2026
|
|
|
|
| 4521 |
]
|
| 4522 |
},
|
| 4523 |
"multimodal.text-to-3d": {
|
| 4524 |
"query": "\"text to 3D\" in:readme",
|
| 4525 |
"years": [
|
| 4526 |
-
2026
|
|
|
|
| 4527 |
]
|
| 4528 |
},
|
| 4529 |
"multimodal.text-to-image": {
|
| 4530 |
"query": "\"text-to-image\" in:description",
|
| 4531 |
"years": [
|
| 4532 |
-
2026
|
|
|
|
| 4533 |
]
|
| 4534 |
},
|
| 4535 |
"multimodal.text-to-video": {
|
| 4536 |
"query": "\"text-to-video\" in:description",
|
| 4537 |
"years": [
|
| 4538 |
-
2026
|
|
|
|
| 4539 |
]
|
| 4540 |
},
|
| 4541 |
"multimodal.video-language-model": {
|
| 4542 |
"query": "\"video language model\" in:readme",
|
| 4543 |
"years": [
|
| 4544 |
-
2026
|
|
|
|
| 4545 |
]
|
| 4546 |
},
|
| 4547 |
"multimodal.video-question-answering": {
|
|
@@ -4688,67 +4798,78 @@
|
|
| 4688 |
"nlp.named-entity-recognition": {
|
| 4689 |
"query": "\"named entity recognition\" in:readme",
|
| 4690 |
"years": [
|
| 4691 |
-
2026
|
|
|
|
| 4692 |
]
|
| 4693 |
},
|
| 4694 |
"nlp.neural-reranking": {
|
| 4695 |
"query": "\"neural reranking\" in:description",
|
| 4696 |
"years": [
|
| 4697 |
-
2026
|
|
|
|
| 4698 |
]
|
| 4699 |
},
|
| 4700 |
"nlp.question-answering": {
|
| 4701 |
"query": "\"question answering\" in:description",
|
| 4702 |
"years": [
|
| 4703 |
-
2026
|
|
|
|
| 4704 |
]
|
| 4705 |
},
|
| 4706 |
"nlp.rag": {
|
| 4707 |
"query": "\"retrieval augmented generation\" in:description",
|
| 4708 |
"years": [
|
| 4709 |
-
2026
|
|
|
|
| 4710 |
]
|
| 4711 |
},
|
| 4712 |
"nlp.semantic-search": {
|
| 4713 |
"query": "\"semantic search\" in:description",
|
| 4714 |
"years": [
|
| 4715 |
-
2026
|
|
|
|
| 4716 |
]
|
| 4717 |
},
|
| 4718 |
"nlp.sentence-embeddings": {
|
| 4719 |
"query": "\"sentence embeddings\" in:description",
|
| 4720 |
"years": [
|
| 4721 |
-
2026
|
|
|
|
| 4722 |
]
|
| 4723 |
},
|
| 4724 |
"nlp.subword-tokenization": {
|
| 4725 |
"query": "\"subword tokenization\" in:readme",
|
| 4726 |
"years": [
|
| 4727 |
-
2026
|
|
|
|
| 4728 |
]
|
| 4729 |
},
|
| 4730 |
"nlp.text-classification": {
|
| 4731 |
"query": "\"text classification\" in:description",
|
| 4732 |
"years": [
|
| 4733 |
-
2026
|
|
|
|
| 4734 |
]
|
| 4735 |
},
|
| 4736 |
"nlp.text-generation": {
|
| 4737 |
"query": "\"text generation\" in:readme",
|
| 4738 |
"years": [
|
| 4739 |
-
2026
|
|
|
|
| 4740 |
]
|
| 4741 |
},
|
| 4742 |
"nlp.text-summarization": {
|
| 4743 |
"query": "\"text summarization\" in:description",
|
| 4744 |
"years": [
|
| 4745 |
-
2026
|
|
|
|
| 4746 |
]
|
| 4747 |
},
|
| 4748 |
"nlp.topic-modeling": {
|
| 4749 |
"query": "\"topic modeling\" in:readme",
|
| 4750 |
"years": [
|
| 4751 |
-
2026
|
|
|
|
| 4752 |
]
|
| 4753 |
},
|
| 4754 |
"recall.archaeological-remote-sensing": {
|
|
@@ -4810,61 +4931,71 @@
|
|
| 4810 |
"recall.epidemiological-modeling": {
|
| 4811 |
"query": "\"epidemiological modeling\" machine learning in:name,description,readme",
|
| 4812 |
"years": [
|
| 4813 |
-
2026
|
|
|
|
| 4814 |
]
|
| 4815 |
},
|
| 4816 |
"recall.grid-stability-prediction": {
|
| 4817 |
"query": "\"grid stability prediction\" in:name,description,readme",
|
| 4818 |
"years": [
|
| 4819 |
-
2026
|
|
|
|
| 4820 |
]
|
| 4821 |
},
|
| 4822 |
"recall.historical-document-recognition": {
|
| 4823 |
"query": "\"historical document recognition\" in:name,description,readme",
|
| 4824 |
"years": [
|
| 4825 |
-
2026
|
|
|
|
| 4826 |
]
|
| 4827 |
},
|
| 4828 |
"recall.infrastructure-damage-detection": {
|
| 4829 |
"query": "\"infrastructure damage detection\" deep learning in:name,description,readme",
|
| 4830 |
"years": [
|
| 4831 |
-
2026
|
|
|
|
| 4832 |
]
|
| 4833 |
},
|
| 4834 |
"recall.insurance-risk-modeling": {
|
| 4835 |
"query": "\"insurance risk\" machine learning in:name,description,readme",
|
| 4836 |
"years": [
|
| 4837 |
-
2026
|
|
|
|
| 4838 |
]
|
| 4839 |
},
|
| 4840 |
"recall.legal-document-classification": {
|
| 4841 |
"query": "\"legal document classification\" in:name,description,readme",
|
| 4842 |
"years": [
|
| 4843 |
-
2026
|
|
|
|
| 4844 |
]
|
| 4845 |
},
|
| 4846 |
"recall.legal-nlp": {
|
| 4847 |
"query": "legal NLP in:name,description,readme",
|
| 4848 |
"years": [
|
| 4849 |
-
2026
|
|
|
|
| 4850 |
]
|
| 4851 |
},
|
| 4852 |
"recall.name.artificial-intelligence": {
|
| 4853 |
"query": "\"artificial intelligence\" in:name,description,readme",
|
| 4854 |
"years": [
|
| 4855 |
-
2026
|
|
|
|
| 4856 |
]
|
| 4857 |
},
|
| 4858 |
"recall.name.deep-learning": {
|
| 4859 |
"query": "\"deep learning\" in:name,description,readme",
|
| 4860 |
"years": [
|
| 4861 |
-
2026
|
|
|
|
| 4862 |
]
|
| 4863 |
},
|
| 4864 |
"recall.name.diffusion-model": {
|
| 4865 |
"query": "diffusion model in:name,description,readme",
|
| 4866 |
"years": [
|
| 4867 |
-
2026
|
|
|
|
| 4868 |
]
|
| 4869 |
},
|
| 4870 |
"recall.name.foundation-model": {
|
|
@@ -5066,61 +5197,71 @@
|
|
| 5066 |
"rl.hierarchical": {
|
| 5067 |
"query": "\"hierarchical reinforcement learning\" in:description",
|
| 5068 |
"years": [
|
| 5069 |
-
2026
|
|
|
|
| 5070 |
]
|
| 5071 |
},
|
| 5072 |
"rl.imitation-learning": {
|
| 5073 |
"query": "\"imitation learning\" in:description",
|
| 5074 |
"years": [
|
| 5075 |
-
2026
|
|
|
|
| 5076 |
]
|
| 5077 |
},
|
| 5078 |
"rl.inverse": {
|
| 5079 |
"query": "\"inverse reinforcement learning\" in:description",
|
| 5080 |
"years": [
|
| 5081 |
-
2026
|
|
|
|
| 5082 |
]
|
| 5083 |
},
|
| 5084 |
"rl.model-based": {
|
| 5085 |
"query": "\"model-based reinforcement learning\" in:description",
|
| 5086 |
"years": [
|
| 5087 |
-
2026
|
|
|
|
| 5088 |
]
|
| 5089 |
},
|
| 5090 |
"rl.model-free": {
|
| 5091 |
"query": "\"model-free reinforcement learning\" in:description",
|
| 5092 |
"years": [
|
| 5093 |
-
2026
|
|
|
|
| 5094 |
]
|
| 5095 |
},
|
| 5096 |
"rl.multiagent": {
|
| 5097 |
"query": "\"multi-agent reinforcement learning\" in:description",
|
| 5098 |
"years": [
|
| 5099 |
-
2026
|
|
|
|
| 5100 |
]
|
| 5101 |
},
|
| 5102 |
"rl.offline": {
|
| 5103 |
"query": "\"offline reinforcement learning\" in:description",
|
| 5104 |
"years": [
|
| 5105 |
-
2026
|
|
|
|
| 5106 |
]
|
| 5107 |
},
|
| 5108 |
"rl.planning": {
|
| 5109 |
"query": "\"reinforcement learning planning\" in:description",
|
| 5110 |
"years": [
|
| 5111 |
-
2026
|
|
|
|
| 5112 |
]
|
| 5113 |
},
|
| 5114 |
"rl.policy-gradient": {
|
| 5115 |
"query": "\"policy gradient\" in:description",
|
| 5116 |
"years": [
|
| 5117 |
-
2026
|
|
|
|
| 5118 |
]
|
| 5119 |
},
|
| 5120 |
"rl.ppo": {
|
| 5121 |
"query": "\"proximal policy optimization\" in:description",
|
| 5122 |
"years": [
|
| 5123 |
-
2026
|
|
|
|
| 5124 |
]
|
| 5125 |
},
|
| 5126 |
"rl.preference": {
|
|
@@ -5206,61 +5347,71 @@
|
|
| 5206 |
"robotics.manipulation": {
|
| 5207 |
"query": "\"robot manipulation\" in:description",
|
| 5208 |
"years": [
|
| 5209 |
-
2026
|
|
|
|
| 5210 |
]
|
| 5211 |
},
|
| 5212 |
"robotics.navigation": {
|
| 5213 |
"query": "\"robot navigation\" in:description",
|
| 5214 |
"years": [
|
| 5215 |
-
2026
|
|
|
|
| 5216 |
]
|
| 5217 |
},
|
| 5218 |
"robotics.robot-control": {
|
| 5219 |
"query": "\"robot control\" in:description",
|
| 5220 |
"years": [
|
| 5221 |
-
2026
|
|
|
|
| 5222 |
]
|
| 5223 |
},
|
| 5224 |
"robotics.robot-foundation-model": {
|
| 5225 |
"query": "robot foundation model in:description,readme",
|
| 5226 |
"years": [
|
| 5227 |
-
2026
|
|
|
|
| 5228 |
]
|
| 5229 |
},
|
| 5230 |
"robotics.robot-learning": {
|
| 5231 |
"query": "\"robot learning\" in:description",
|
| 5232 |
"years": [
|
| 5233 |
-
2026
|
|
|
|
| 5234 |
]
|
| 5235 |
},
|
| 5236 |
"robotics.robot-manipulation-learning": {
|
| 5237 |
"query": "\"robot manipulation learning\" in:readme",
|
| 5238 |
"years": [
|
| 5239 |
-
2026
|
|
|
|
| 5240 |
]
|
| 5241 |
},
|
| 5242 |
"robotics.robot-motion-planning": {
|
| 5243 |
"query": "\"robot motion planning\" in:description",
|
| 5244 |
"years": [
|
| 5245 |
-
2026
|
|
|
|
| 5246 |
]
|
| 5247 |
},
|
| 5248 |
"robotics.robotics-reinforcement-learning": {
|
| 5249 |
"query": "\"robotics reinforcement learning\" in:description",
|
| 5250 |
"years": [
|
| 5251 |
-
2026
|
|
|
|
| 5252 |
]
|
| 5253 |
},
|
| 5254 |
"robotics.robotics-topic": {
|
| 5255 |
"query": "topic:robotics",
|
| 5256 |
"years": [
|
| 5257 |
-
2026
|
|
|
|
| 5258 |
]
|
| 5259 |
},
|
| 5260 |
"robotics.sim2real": {
|
| 5261 |
"query": "\"sim-to-real\" in:description",
|
| 5262 |
"years": [
|
| 5263 |
-
2026
|
|
|
|
| 5264 |
]
|
| 5265 |
},
|
| 5266 |
"robotics.slam": {
|
|
@@ -5352,61 +5503,71 @@
|
|
| 5352 |
"science.fusion-plasma": {
|
| 5353 |
"query": "fusion plasma in:description \"machine learning\"",
|
| 5354 |
"years": [
|
| 5355 |
-
2026
|
|
|
|
| 5356 |
]
|
| 5357 |
},
|
| 5358 |
"science.gravitational-waves": {
|
| 5359 |
"query": "\"gravitational wave\" \"machine learning\" in:description,readme",
|
| 5360 |
"years": [
|
| 5361 |
-
2026
|
|
|
|
| 5362 |
]
|
| 5363 |
},
|
| 5364 |
"science.inverse-problems": {
|
| 5365 |
"query": "\"inverse problems\" in:description",
|
| 5366 |
"years": [
|
| 5367 |
-
2026
|
|
|
|
| 5368 |
]
|
| 5369 |
},
|
| 5370 |
"science.neural-operators": {
|
| 5371 |
"query": "\"neural operator\" in:description",
|
| 5372 |
"years": [
|
| 5373 |
-
2026
|
|
|
|
| 5374 |
]
|
| 5375 |
},
|
| 5376 |
"science.ocean-modeling": {
|
| 5377 |
"query": "\"ocean modeling\" \"machine learning\" in:description,readme",
|
| 5378 |
"years": [
|
| 5379 |
-
2026
|
|
|
|
| 5380 |
]
|
| 5381 |
},
|
| 5382 |
"science.particle-physics": {
|
| 5383 |
"query": "\"particle physics\" in:description",
|
| 5384 |
"years": [
|
| 5385 |
-
2026
|
|
|
|
| 5386 |
]
|
| 5387 |
},
|
| 5388 |
"science.photonics": {
|
| 5389 |
"query": "photonics \"machine learning\" in:description,readme",
|
| 5390 |
"years": [
|
| 5391 |
-
2026
|
|
|
|
| 5392 |
]
|
| 5393 |
},
|
| 5394 |
"science.physics": {
|
| 5395 |
"query": "physics in:description",
|
| 5396 |
"years": [
|
| 5397 |
-
2026
|
|
|
|
| 5398 |
]
|
| 5399 |
},
|
| 5400 |
"science.physics-informed-neural-networks": {
|
| 5401 |
"query": "\"physics-informed neural network\" in:description",
|
| 5402 |
"years": [
|
| 5403 |
-
2026
|
|
|
|
| 5404 |
]
|
| 5405 |
},
|
| 5406 |
"science.plasma-physics": {
|
| 5407 |
"query": "\"plasma physics\" in:description",
|
| 5408 |
"years": [
|
| 5409 |
-
2026
|
|
|
|
| 5410 |
]
|
| 5411 |
},
|
| 5412 |
"science.quantum-materials": {
|
|
@@ -5516,43 +5677,50 @@
|
|
| 5516 |
"specialized.fmri-decoding-ml": {
|
| 5517 |
"query": "\"fMRI decoding\" \"machine learning\" in:description,readme",
|
| 5518 |
"years": [
|
| 5519 |
-
2026
|
|
|
|
| 5520 |
]
|
| 5521 |
},
|
| 5522 |
"specialized.machine-unlearning": {
|
| 5523 |
"query": "\"machine unlearning\" in:description,readme",
|
| 5524 |
"years": [
|
| 5525 |
-
2026
|
|
|
|
| 5526 |
]
|
| 5527 |
},
|
| 5528 |
"specialized.mechanistic-interpretability": {
|
| 5529 |
"query": "\"mechanistic interpretability\" in:description,readme",
|
| 5530 |
"years": [
|
| 5531 |
-
2026
|
|
|
|
| 5532 |
]
|
| 5533 |
},
|
| 5534 |
"specialized.medical-image-registration-deep-learning": {
|
| 5535 |
"query": "\"medical image registration\" \"deep learning\" in:description,readme",
|
| 5536 |
"years": [
|
| 5537 |
-
2026
|
|
|
|
| 5538 |
]
|
| 5539 |
},
|
| 5540 |
"specialized.pathology-foundation-model": {
|
| 5541 |
"query": "\"pathology foundation model\" \"machine learning\" in:description,readme",
|
| 5542 |
"years": [
|
| 5543 |
-
2026
|
|
|
|
| 5544 |
]
|
| 5545 |
},
|
| 5546 |
"specialized.spiking-neural-network": {
|
| 5547 |
"query": "\"spiking neural network\" in:description,readme",
|
| 5548 |
"years": [
|
| 5549 |
-
2026
|
|
|
|
| 5550 |
]
|
| 5551 |
},
|
| 5552 |
"specialized.test-time-adaptation": {
|
| 5553 |
"query": "\"test-time adaptation\" in:description,readme",
|
| 5554 |
"years": [
|
| 5555 |
-
2026
|
|
|
|
| 5556 |
]
|
| 5557 |
},
|
| 5558 |
"timeseries.anomaly-detection": {
|
|
@@ -5614,61 +5782,71 @@
|
|
| 5614 |
"timeseries.long-horizon": {
|
| 5615 |
"query": "\"long horizon forecasting\" in:readme",
|
| 5616 |
"years": [
|
| 5617 |
-
2026
|
|
|
|
| 5618 |
]
|
| 5619 |
},
|
| 5620 |
"timeseries.multivariate": {
|
| 5621 |
"query": "\"multivariate time series\" in:description",
|
| 5622 |
"years": [
|
| 5623 |
-
2026
|
|
|
|
| 5624 |
]
|
| 5625 |
},
|
| 5626 |
"timeseries.nbeats": {
|
| 5627 |
"query": "N-BEATS in:description",
|
| 5628 |
"years": [
|
| 5629 |
-
2026
|
|
|
|
| 5630 |
]
|
| 5631 |
},
|
| 5632 |
"timeseries.patchtst": {
|
| 5633 |
"query": "PatchTST in:description",
|
| 5634 |
"years": [
|
| 5635 |
-
2026
|
|
|
|
| 5636 |
]
|
| 5637 |
},
|
| 5638 |
"timeseries.predictive-maintenance": {
|
| 5639 |
"query": "\"predictive maintenance\" in:description",
|
| 5640 |
"years": [
|
| 5641 |
-
2026
|
|
|
|
| 5642 |
]
|
| 5643 |
},
|
| 5644 |
"timeseries.probabilistic-forecasting": {
|
| 5645 |
"query": "\"probabilistic forecasting\" in:readme",
|
| 5646 |
"years": [
|
| 5647 |
-
2026
|
|
|
|
| 5648 |
]
|
| 5649 |
},
|
| 5650 |
"timeseries.remaining-useful-life": {
|
| 5651 |
"query": "\"remaining useful life\" in:readme",
|
| 5652 |
"years": [
|
| 5653 |
-
2026
|
|
|
|
| 5654 |
]
|
| 5655 |
},
|
| 5656 |
"timeseries.sensor-data": {
|
| 5657 |
"query": "\"sensor time series\" in:description",
|
| 5658 |
"years": [
|
| 5659 |
-
2026
|
|
|
|
| 5660 |
]
|
| 5661 |
},
|
| 5662 |
"timeseries.state-space-models": {
|
| 5663 |
"query": "\"state space model\" in:description",
|
| 5664 |
"years": [
|
| 5665 |
-
2026
|
|
|
|
| 5666 |
]
|
| 5667 |
},
|
| 5668 |
"timeseries.streaming": {
|
| 5669 |
"query": "\"streaming time series\" in:readme",
|
| 5670 |
"years": [
|
| 5671 |
-
2026
|
|
|
|
| 5672 |
]
|
| 5673 |
},
|
| 5674 |
"timeseries.synthetic-generation": {
|
|
@@ -5771,67 +5949,78 @@
|
|
| 5771 |
"trust.causal-mediation": {
|
| 5772 |
"query": "\"causal mediation analysis\" in:description",
|
| 5773 |
"years": [
|
| 5774 |
-
2026
|
|
|
|
| 5775 |
]
|
| 5776 |
},
|
| 5777 |
"trust.causal-ml": {
|
| 5778 |
"query": "\"causal machine learning\" in:description",
|
| 5779 |
"years": [
|
| 5780 |
-
2026
|
|
|
|
| 5781 |
]
|
| 5782 |
},
|
| 5783 |
"trust.causal-representation-learning": {
|
| 5784 |
"query": "\"causal representation learning\" in:description",
|
| 5785 |
"years": [
|
| 5786 |
-
2026
|
|
|
|
| 5787 |
]
|
| 5788 |
},
|
| 5789 |
"trust.conformal-prediction": {
|
| 5790 |
"query": "\"conformal prediction\" in:description",
|
| 5791 |
"years": [
|
| 5792 |
-
2026
|
|
|
|
| 5793 |
]
|
| 5794 |
},
|
| 5795 |
"trust.counterfactual-explanations": {
|
| 5796 |
"query": "\"counterfactual explanation\" in:description",
|
| 5797 |
"years": [
|
| 5798 |
-
2026
|
|
|
|
| 5799 |
]
|
| 5800 |
},
|
| 5801 |
"trust.differential-privacy": {
|
| 5802 |
"query": "\"differential privacy\" in:description",
|
| 5803 |
"years": [
|
| 5804 |
-
2026
|
|
|
|
| 5805 |
]
|
| 5806 |
},
|
| 5807 |
"trust.distribution-shift": {
|
| 5808 |
"query": "\"distribution shift\" in:description",
|
| 5809 |
"years": [
|
| 5810 |
-
2026
|
|
|
|
| 5811 |
]
|
| 5812 |
},
|
| 5813 |
"trust.domain-generalization": {
|
| 5814 |
"query": "\"domain generalization\" in:description",
|
| 5815 |
"years": [
|
| 5816 |
-
2026
|
|
|
|
| 5817 |
]
|
| 5818 |
},
|
| 5819 |
"trust.explainable-ai": {
|
| 5820 |
"query": "\"explainable AI\" in:description",
|
| 5821 |
"years": [
|
| 5822 |
-
2026
|
|
|
|
| 5823 |
]
|
| 5824 |
},
|
| 5825 |
"trust.federated-learning": {
|
| 5826 |
"query": "\"federated learning\" in:description",
|
| 5827 |
"years": [
|
| 5828 |
-
2026
|
|
|
|
| 5829 |
]
|
| 5830 |
},
|
| 5831 |
"trust.instrumental-variable-ml": {
|
| 5832 |
"query": "\"double machine learning\" in:description",
|
| 5833 |
"years": [
|
| 5834 |
-
2026
|
|
|
|
| 5835 |
]
|
| 5836 |
},
|
| 5837 |
"trust.interpretable-ml": {
|
|
@@ -5952,67 +6141,78 @@
|
|
| 5952 |
"vision.image-restoration": {
|
| 5953 |
"query": "\"image restoration\" in:readme",
|
| 5954 |
"years": [
|
| 5955 |
-
2026
|
|
|
|
| 5956 |
]
|
| 5957 |
},
|
| 5958 |
"vision.image-retrieval": {
|
| 5959 |
"query": "\"image retrieval\" in:readme",
|
| 5960 |
"years": [
|
| 5961 |
-
2026
|
|
|
|
| 5962 |
]
|
| 5963 |
},
|
| 5964 |
"vision.image-super-resolution": {
|
| 5965 |
"query": "\"image super-resolution\" in:readme",
|
| 5966 |
"years": [
|
| 5967 |
-
2026
|
|
|
|
| 5968 |
]
|
| 5969 |
},
|
| 5970 |
"vision.image-to-image-translation": {
|
| 5971 |
"query": "\"image-to-image translation\" in:readme",
|
| 5972 |
"years": [
|
| 5973 |
-
2026
|
|
|
|
| 5974 |
]
|
| 5975 |
},
|
| 5976 |
"vision.neural-rendering": {
|
| 5977 |
"query": "\"neural rendering\" in:description",
|
| 5978 |
"years": [
|
| 5979 |
-
2026
|
|
|
|
| 5980 |
]
|
| 5981 |
},
|
| 5982 |
"vision.object-detection": {
|
| 5983 |
"query": "\"object detection\" in:description",
|
| 5984 |
"years": [
|
| 5985 |
-
2026
|
|
|
|
| 5986 |
]
|
| 5987 |
},
|
| 5988 |
"vision.object-tracking": {
|
| 5989 |
"query": "\"object tracking\" in:readme",
|
| 5990 |
"years": [
|
| 5991 |
-
2026
|
|
|
|
| 5992 |
]
|
| 5993 |
},
|
| 5994 |
"vision.ocr": {
|
| 5995 |
"query": "topic:ocr",
|
| 5996 |
"years": [
|
| 5997 |
-
2026
|
|
|
|
| 5998 |
]
|
| 5999 |
},
|
| 6000 |
"vision.open-vocabulary-detection": {
|
| 6001 |
"query": "\"open-vocabulary detection\" in:readme",
|
| 6002 |
"years": [
|
| 6003 |
-
2026
|
|
|
|
| 6004 |
]
|
| 6005 |
},
|
| 6006 |
"vision.optical-flow": {
|
| 6007 |
"query": "topic:optical-flow",
|
| 6008 |
"years": [
|
| 6009 |
-
2026
|
|
|
|
| 6010 |
]
|
| 6011 |
},
|
| 6012 |
"vision.pose-estimation": {
|
| 6013 |
"query": "\"human pose estimation\" in:readme",
|
| 6014 |
"years": [
|
| 6015 |
-
2026
|
|
|
|
| 6016 |
]
|
| 6017 |
},
|
| 6018 |
"vision.promptable-segmentation": {
|
|
@@ -6079,5 +6279,5 @@
|
|
| 6079 |
"end": "2026-09-24",
|
| 6080 |
"search_policy_version": 2,
|
| 6081 |
"start_year": 2008,
|
| 6082 |
-
"updated_at": "2026-09-
|
| 6083 |
}
|
|
|
|
| 2401 |
"applied.customer-lifetime-value": {
|
| 2402 |
"query": "\"customer lifetime value\" in:description",
|
| 2403 |
"years": [
|
| 2404 |
+
2026,
|
| 2405 |
+
2025
|
| 2406 |
]
|
| 2407 |
},
|
| 2408 |
"applied.customer-segmentation": {
|
| 2409 |
"query": "\"customer segmentation\" \"machine learning\" in:description,readme",
|
| 2410 |
"years": [
|
| 2411 |
+
2026,
|
| 2412 |
+
2025
|
| 2413 |
]
|
| 2414 |
},
|
| 2415 |
"applied.cybersecurity-ml": {
|
| 2416 |
"query": "\"machine learning\" cybersecurity in:description,readme",
|
| 2417 |
"years": [
|
| 2418 |
+
2026,
|
| 2419 |
+
2025
|
| 2420 |
]
|
| 2421 |
},
|
| 2422 |
"applied.demand-forecasting": {
|
| 2423 |
"query": "\"demand forecasting\" in:description",
|
| 2424 |
"years": [
|
| 2425 |
+
2026,
|
| 2426 |
+
2025
|
| 2427 |
]
|
| 2428 |
},
|
| 2429 |
"applied.dynamic-pricing": {
|
| 2430 |
"query": "\"dynamic pricing\" \"machine learning\" in:description,readme",
|
| 2431 |
"years": [
|
| 2432 |
+
2026,
|
| 2433 |
+
2025
|
| 2434 |
]
|
| 2435 |
},
|
| 2436 |
"applied.ecological-forecasting": {
|
| 2437 |
"query": "\"ecological forecasting\" \"machine learning\" in:description,readme",
|
| 2438 |
"years": [
|
| 2439 |
+
2026,
|
| 2440 |
+
2025
|
| 2441 |
]
|
| 2442 |
},
|
| 2443 |
"applied.educational-data-mining": {
|
| 2444 |
"query": "\"educational data mining\" in:description,readme",
|
| 2445 |
"years": [
|
| 2446 |
+
2026,
|
| 2447 |
+
2025
|
| 2448 |
]
|
| 2449 |
},
|
| 2450 |
"applied.energy-load-forecasting": {
|
| 2451 |
"query": "\"load forecasting\" energy in:description,readme",
|
| 2452 |
"years": [
|
| 2453 |
+
2026,
|
| 2454 |
+
2025
|
| 2455 |
]
|
| 2456 |
},
|
| 2457 |
"applied.fraud-detection": {
|
| 2458 |
"query": "\"fraud detection\" \"machine learning\" in:description,readme",
|
| 2459 |
"years": [
|
| 2460 |
+
2026,
|
| 2461 |
+
2025
|
| 2462 |
]
|
| 2463 |
},
|
| 2464 |
"applied.industrial-defect-detection": {
|
| 2465 |
"query": "\"industrial defect detection\" \"deep learning\" in:description,readme",
|
| 2466 |
"years": [
|
| 2467 |
+
2026,
|
| 2468 |
+
2025
|
| 2469 |
]
|
| 2470 |
},
|
| 2471 |
"applied.intrusion-detection": {
|
| 2472 |
"query": "\"intrusion detection\" \"machine learning\" in:description,readme",
|
| 2473 |
"years": [
|
| 2474 |
+
2026,
|
| 2475 |
+
2025
|
| 2476 |
]
|
| 2477 |
},
|
| 2478 |
"applied.inventory-optimization": {
|
|
|
|
| 2825 |
"bio.metagenomics": {
|
| 2826 |
"query": "\"metagenomic classification\" in:description,readme",
|
| 2827 |
"years": [
|
| 2828 |
+
2026,
|
| 2829 |
+
2025
|
| 2830 |
]
|
| 2831 |
},
|
| 2832 |
"bio.microbiome": {
|
| 2833 |
"query": "\"microbiome\" \"machine learning\" in:description,readme",
|
| 2834 |
"years": [
|
| 2835 |
+
2026,
|
| 2836 |
+
2025
|
| 2837 |
]
|
| 2838 |
},
|
| 2839 |
"bio.microscopy-cell-analysis": {
|
| 2840 |
"query": "\"cell segmentation\" microscopy in:description,readme",
|
| 2841 |
"years": [
|
| 2842 |
+
2026,
|
| 2843 |
+
2025
|
| 2844 |
]
|
| 2845 |
},
|
| 2846 |
"bio.molecular-dynamics": {
|
| 2847 |
"query": "\"molecular dynamics\" in:description",
|
| 2848 |
"years": [
|
| 2849 |
+
2026,
|
| 2850 |
+
2025
|
| 2851 |
]
|
| 2852 |
},
|
| 2853 |
"bio.molecular-force-fields": {
|
| 2854 |
"query": "\"machine learning force field\" in:readme",
|
| 2855 |
"years": [
|
| 2856 |
+
2026,
|
| 2857 |
+
2025
|
| 2858 |
]
|
| 2859 |
},
|
| 2860 |
"bio.phylogenetics": {
|
| 2861 |
"query": "\"phylogenetics\" in:description",
|
| 2862 |
"years": [
|
| 2863 |
+
2026,
|
| 2864 |
+
2025
|
| 2865 |
]
|
| 2866 |
},
|
| 2867 |
"bio.protein-design": {
|
| 2868 |
"query": "\"protein design\" in:description",
|
| 2869 |
"years": [
|
| 2870 |
+
2026,
|
| 2871 |
+
2025
|
| 2872 |
]
|
| 2873 |
},
|
| 2874 |
"bio.protein-folding": {
|
| 2875 |
"query": "\"protein folding\" in:readme",
|
| 2876 |
"years": [
|
| 2877 |
+
2026,
|
| 2878 |
+
2025
|
| 2879 |
]
|
| 2880 |
},
|
| 2881 |
"bio.protein-interactions": {
|
| 2882 |
"query": "\"protein-protein interaction prediction\" in:readme",
|
| 2883 |
"years": [
|
| 2884 |
+
2026,
|
| 2885 |
+
2025
|
| 2886 |
]
|
| 2887 |
},
|
| 2888 |
"bio.protein-structure": {
|
| 2889 |
"query": "\"protein structure prediction\" in:description",
|
| 2890 |
"years": [
|
| 2891 |
+
2026,
|
| 2892 |
+
2025
|
| 2893 |
]
|
| 2894 |
},
|
| 2895 |
"bio.regulatory-sequence-modeling": {
|
| 2896 |
"query": "enhancer prediction genomics in:description,readme",
|
| 2897 |
"years": [
|
| 2898 |
+
2026,
|
| 2899 |
+
2025
|
| 2900 |
]
|
| 2901 |
},
|
| 2902 |
"bio.rna-language-models": {
|
|
|
|
| 3140 |
"efficiency.gpu-kernels": {
|
| 3141 |
"query": "\"GPU kernel\" in:description",
|
| 3142 |
"years": [
|
| 3143 |
+
2026,
|
| 3144 |
+
2025
|
| 3145 |
]
|
| 3146 |
},
|
| 3147 |
"efficiency.gradient-optimization": {
|
| 3148 |
"query": "\"gradient-based optimization\" in:description",
|
| 3149 |
"years": [
|
| 3150 |
+
2026,
|
| 3151 |
+
2025
|
| 3152 |
]
|
| 3153 |
},
|
| 3154 |
"efficiency.hyperparameter-optimization": {
|
| 3155 |
"query": "\"hyperparameter optimization\" in:description",
|
| 3156 |
"years": [
|
| 3157 |
+
2026,
|
| 3158 |
+
2025
|
| 3159 |
]
|
| 3160 |
},
|
| 3161 |
"efficiency.inference-systems": {
|
| 3162 |
"query": "\"inference engine\" \"machine learning\" in:description,readme",
|
| 3163 |
"years": [
|
| 3164 |
+
2026,
|
| 3165 |
+
2025
|
| 3166 |
]
|
| 3167 |
},
|
| 3168 |
"efficiency.knowledge-distillation": {
|
| 3169 |
"query": "\"knowledge distillation\" in:description",
|
| 3170 |
"years": [
|
| 3171 |
+
2026,
|
| 3172 |
+
2025
|
| 3173 |
]
|
| 3174 |
},
|
| 3175 |
"efficiency.kv-cache": {
|
| 3176 |
"query": "\"KV cache\" in:description",
|
| 3177 |
"years": [
|
| 3178 |
+
2026,
|
| 3179 |
+
2025
|
| 3180 |
]
|
| 3181 |
},
|
| 3182 |
"efficiency.lora": {
|
| 3183 |
"query": "LoRA in:description",
|
| 3184 |
"years": [
|
| 3185 |
+
2026,
|
| 3186 |
+
2025
|
| 3187 |
]
|
| 3188 |
},
|
| 3189 |
"efficiency.low-rank-factorization": {
|
| 3190 |
"query": "\"low-rank factorization\" in:description",
|
| 3191 |
"years": [
|
| 3192 |
+
2026,
|
| 3193 |
+
2025
|
| 3194 |
]
|
| 3195 |
},
|
| 3196 |
"efficiency.mixed-precision-training": {
|
| 3197 |
"query": "\"mixed precision training\" in:description",
|
| 3198 |
"years": [
|
| 3199 |
+
2026,
|
| 3200 |
+
2025
|
| 3201 |
]
|
| 3202 |
},
|
| 3203 |
"efficiency.mixture-of-experts": {
|
| 3204 |
"query": "\"mixture of experts\" in:description",
|
| 3205 |
"years": [
|
| 3206 |
+
2026,
|
| 3207 |
+
2025
|
| 3208 |
]
|
| 3209 |
},
|
| 3210 |
"efficiency.model-compression": {
|
| 3211 |
"query": "\"model compression\" in:description",
|
| 3212 |
"years": [
|
| 3213 |
+
2026,
|
| 3214 |
+
2025
|
| 3215 |
]
|
| 3216 |
},
|
| 3217 |
"efficiency.neural-architecture-search": {
|
|
|
|
| 3327 |
"gap2026.econometrics-double-ml": {
|
| 3328 |
"query": "\"double machine learning\" econometrics in:description,readme",
|
| 3329 |
"years": [
|
| 3330 |
+
2026,
|
| 3331 |
+
2025
|
| 3332 |
]
|
| 3333 |
},
|
| 3334 |
"gap2026.econometrics-heterogeneous-effects": {
|
| 3335 |
"query": "\"heterogeneous treatment effects\" machine learning economics in:description,readme",
|
| 3336 |
"years": [
|
| 3337 |
+
2026,
|
| 3338 |
+
2025
|
| 3339 |
]
|
| 3340 |
},
|
| 3341 |
"gap2026.econometrics-policy-learning": {
|
| 3342 |
"query": "\"policy learning\" causal machine learning economics in:description,readme",
|
| 3343 |
"years": [
|
| 3344 |
+
2026,
|
| 3345 |
+
2025
|
| 3346 |
]
|
| 3347 |
},
|
| 3348 |
"gap2026.forecasting-count-data": {
|
| 3349 |
"query": "\"count time series forecasting\" neural in:description,readme",
|
| 3350 |
"years": [
|
| 3351 |
+
2026,
|
| 3352 |
+
2025
|
| 3353 |
]
|
| 3354 |
},
|
| 3355 |
"gap2026.forecasting-hierarchical": {
|
| 3356 |
"query": "\"hierarchical time series forecasting\" machine learning in:description,readme",
|
| 3357 |
"years": [
|
| 3358 |
+
2026,
|
| 3359 |
+
2025
|
| 3360 |
]
|
| 3361 |
},
|
| 3362 |
"gap2026.forecasting-intermittent-demand": {
|
| 3363 |
"query": "\"intermittent demand forecasting\" machine learning in:description,readme",
|
| 3364 |
"years": [
|
| 3365 |
+
2026,
|
| 3366 |
+
2025
|
| 3367 |
]
|
| 3368 |
},
|
| 3369 |
"gap2026.forecasting-quantile": {
|
| 3370 |
"query": "\"neural quantile forecasting\" in:description,readme",
|
| 3371 |
"years": [
|
| 3372 |
+
2026,
|
| 3373 |
+
2025
|
| 3374 |
]
|
| 3375 |
},
|
| 3376 |
"gap2026.green-ai-carbon": {
|
| 3377 |
"query": "\"carbon emissions\" machine learning training in:description,readme",
|
| 3378 |
"years": [
|
| 3379 |
+
2026,
|
| 3380 |
+
2025
|
| 3381 |
]
|
| 3382 |
},
|
| 3383 |
"gap2026.green-ai-carbon-aware-scheduling": {
|
| 3384 |
"query": "\"carbon-aware\" machine learning scheduling in:description,readme",
|
| 3385 |
"years": [
|
| 3386 |
+
2026,
|
| 3387 |
+
2025
|
| 3388 |
]
|
| 3389 |
},
|
| 3390 |
"gap2026.green-ai-efficient-inference": {
|
| 3391 |
"query": "\"energy efficient inference\" neural network in:description,readme",
|
| 3392 |
"years": [
|
| 3393 |
+
2026,
|
| 3394 |
+
2025
|
| 3395 |
]
|
| 3396 |
},
|
| 3397 |
"gap2026.green-ai-energy": {
|
| 3398 |
"query": "\"energy efficient machine learning\" in:description,readme",
|
| 3399 |
"years": [
|
| 3400 |
+
2026,
|
| 3401 |
+
2025
|
| 3402 |
]
|
| 3403 |
},
|
| 3404 |
"gap2026.math-learned-optimization": {
|
|
|
|
| 3520 |
"general.contrastive-learning": {
|
| 3521 |
"query": "\"contrastive learning\" in:description,readme",
|
| 3522 |
"years": [
|
| 3523 |
+
2026,
|
| 3524 |
+
2025
|
| 3525 |
]
|
| 3526 |
},
|
| 3527 |
"general.decision-trees": {
|
| 3528 |
"query": "\"decision tree\" \"machine learning\" in:description,readme",
|
| 3529 |
"years": [
|
| 3530 |
+
2026,
|
| 3531 |
+
2025
|
| 3532 |
]
|
| 3533 |
},
|
| 3534 |
"general.deep-learning-description": {
|
| 3535 |
"query": "\"deep learning\" in:description",
|
| 3536 |
"years": [
|
| 3537 |
+
2026,
|
| 3538 |
+
2025
|
| 3539 |
]
|
| 3540 |
},
|
| 3541 |
"general.deep-learning-readme": {
|
| 3542 |
"query": "\"deep learning\" in:readme",
|
| 3543 |
"years": [
|
| 3544 |
+
2026,
|
| 3545 |
+
2025
|
| 3546 |
]
|
| 3547 |
},
|
| 3548 |
"general.dimensionality-reduction": {
|
| 3549 |
"query": "\"dimensionality reduction\" in:description,readme",
|
| 3550 |
"years": [
|
| 3551 |
+
2026,
|
| 3552 |
+
2025
|
| 3553 |
]
|
| 3554 |
},
|
| 3555 |
"general.domain-adaptation": {
|
| 3556 |
"query": "\"domain adaptation\" \"machine learning\" in:description,readme",
|
| 3557 |
"years": [
|
| 3558 |
+
2026,
|
| 3559 |
+
2025
|
| 3560 |
]
|
| 3561 |
},
|
| 3562 |
"general.gaussian-mixture-models": {
|
| 3563 |
"query": "\"Gaussian mixture model\" in:description,readme",
|
| 3564 |
"years": [
|
| 3565 |
+
2026,
|
| 3566 |
+
2025
|
| 3567 |
]
|
| 3568 |
},
|
| 3569 |
"general.gaussian-process": {
|
| 3570 |
"query": "\"Gaussian process\" in:description",
|
| 3571 |
"years": [
|
| 3572 |
+
2026,
|
| 3573 |
+
2025
|
| 3574 |
]
|
| 3575 |
},
|
| 3576 |
"general.gradient-boosting": {
|
| 3577 |
"query": "\"gradient boosting\" in:description",
|
| 3578 |
"years": [
|
| 3579 |
+
2026,
|
| 3580 |
+
2025
|
| 3581 |
]
|
| 3582 |
},
|
| 3583 |
"general.hidden-markov-models": {
|
| 3584 |
"query": "\"hidden Markov model\" \"machine learning\" in:description,readme",
|
| 3585 |
"years": [
|
| 3586 |
+
2026,
|
| 3587 |
+
2025
|
| 3588 |
]
|
| 3589 |
},
|
| 3590 |
"general.logistic-regression": {
|
| 3591 |
"query": "\"logistic regression\" in:description,readme",
|
| 3592 |
"years": [
|
| 3593 |
+
2026,
|
| 3594 |
+
2025
|
| 3595 |
]
|
| 3596 |
},
|
| 3597 |
"general.machine-learning-description": {
|
|
|
|
| 3803 |
"geo.geospatial-foundation-models": {
|
| 3804 |
"query": "\"geospatial foundation model\" in:readme",
|
| 3805 |
"years": [
|
| 3806 |
+
2026,
|
| 3807 |
+
2025
|
| 3808 |
]
|
| 3809 |
},
|
| 3810 |
"geo.geospatial-knowledge-graph": {
|
| 3811 |
"query": "\"geospatial knowledge graph\" in:description,readme",
|
| 3812 |
"years": [
|
| 3813 |
+
2026,
|
| 3814 |
+
2025
|
| 3815 |
]
|
| 3816 |
},
|
| 3817 |
"geo.hydrology": {
|
| 3818 |
"query": "\"hydrology machine learning\" in:readme",
|
| 3819 |
"years": [
|
| 3820 |
+
2026,
|
| 3821 |
+
2025
|
| 3822 |
]
|
| 3823 |
},
|
| 3824 |
"geo.land-cover": {
|
| 3825 |
"query": "\"land cover\" in:readme",
|
| 3826 |
"years": [
|
| 3827 |
+
2026,
|
| 3828 |
+
2025
|
| 3829 |
]
|
| 3830 |
},
|
| 3831 |
"geo.land-use": {
|
| 3832 |
"query": "\"land use\" in:readme",
|
| 3833 |
"years": [
|
| 3834 |
+
2026,
|
| 3835 |
+
2025
|
| 3836 |
]
|
| 3837 |
},
|
| 3838 |
"geo.lidar": {
|
| 3839 |
"query": "LiDAR in:description \"deep learning\"",
|
| 3840 |
"years": [
|
| 3841 |
+
2026,
|
| 3842 |
+
2025
|
| 3843 |
]
|
| 3844 |
},
|
| 3845 |
"geo.mobility-modeling": {
|
| 3846 |
"query": "\"human mobility\" \"machine learning\" in:description,readme",
|
| 3847 |
"years": [
|
| 3848 |
+
2026,
|
| 3849 |
+
2025
|
| 3850 |
]
|
| 3851 |
},
|
| 3852 |
"geo.object-detection": {
|
| 3853 |
"query": "\"object detection\" \"remote sensing\" in:description,readme",
|
| 3854 |
"years": [
|
| 3855 |
+
2026,
|
| 3856 |
+
2025
|
| 3857 |
]
|
| 3858 |
},
|
| 3859 |
"geo.ocean-remote-sensing": {
|
| 3860 |
"query": "\"ocean remote sensing\" in:description,readme",
|
| 3861 |
"years": [
|
| 3862 |
+
2026,
|
| 3863 |
+
2025
|
| 3864 |
]
|
| 3865 |
},
|
| 3866 |
"geo.precipitation-forecasting": {
|
| 3867 |
"query": "\"precipitation forecasting\" in:description,readme",
|
| 3868 |
"years": [
|
| 3869 |
+
2026,
|
| 3870 |
+
2025
|
| 3871 |
]
|
| 3872 |
},
|
| 3873 |
"geo.sar-imagery": {
|
| 3874 |
"query": "\"synthetic aperture radar\" in:readme",
|
| 3875 |
"years": [
|
| 3876 |
+
2026,
|
| 3877 |
+
2025
|
| 3878 |
]
|
| 3879 |
},
|
| 3880 |
"geo.satellite-imagery": {
|
|
|
|
| 3984 |
"graph.graph-foundation-model": {
|
| 3985 |
"query": "\"graph foundation model\" in:description",
|
| 3986 |
"years": [
|
| 3987 |
+
2026,
|
| 3988 |
+
2025
|
| 3989 |
]
|
| 3990 |
},
|
| 3991 |
"graph.graph-generation": {
|
| 3992 |
"query": "\"graph generation\" in:readme",
|
| 3993 |
"years": [
|
| 3994 |
+
2026,
|
| 3995 |
+
2025
|
| 3996 |
]
|
| 3997 |
},
|
| 3998 |
"graph.graph-transformer": {
|
| 3999 |
"query": "\"graph transformer\" in:description",
|
| 4000 |
"years": [
|
| 4001 |
+
2026,
|
| 4002 |
+
2025
|
| 4003 |
]
|
| 4004 |
},
|
| 4005 |
"graph.hypergraph-neural-network": {
|
| 4006 |
"query": "\"hypergraph neural network\" in:description",
|
| 4007 |
"years": [
|
| 4008 |
+
2026,
|
| 4009 |
+
2025
|
| 4010 |
]
|
| 4011 |
},
|
| 4012 |
"graph.knowledge-graph-embedding": {
|
| 4013 |
"query": "\"knowledge graph embedding\" in:description",
|
| 4014 |
"years": [
|
| 4015 |
+
2026,
|
| 4016 |
+
2025
|
| 4017 |
]
|
| 4018 |
},
|
| 4019 |
"graph.knowledge-graphs": {
|
| 4020 |
"query": "topic:knowledge-graph",
|
| 4021 |
"years": [
|
| 4022 |
+
2026,
|
| 4023 |
+
2025
|
| 4024 |
]
|
| 4025 |
},
|
| 4026 |
"graph.link-prediction": {
|
| 4027 |
"query": "\"link prediction\" in:description",
|
| 4028 |
"years": [
|
| 4029 |
+
2026,
|
| 4030 |
+
2025
|
| 4031 |
]
|
| 4032 |
},
|
| 4033 |
"graph.manifold-learning": {
|
| 4034 |
"query": "\"manifold learning\" in:description",
|
| 4035 |
"years": [
|
| 4036 |
+
2026,
|
| 4037 |
+
2025
|
| 4038 |
]
|
| 4039 |
},
|
| 4040 |
"graph.mesh-graph-learning": {
|
| 4041 |
"query": "\"mesh graph neural network\" in:description",
|
| 4042 |
"years": [
|
| 4043 |
+
2026,
|
| 4044 |
+
2025
|
| 4045 |
]
|
| 4046 |
},
|
| 4047 |
"graph.molecular-graphs": {
|
| 4048 |
"query": "\"molecular graph neural network\" in:readme",
|
| 4049 |
"years": [
|
| 4050 |
+
2026,
|
| 4051 |
+
2025
|
| 4052 |
]
|
| 4053 |
},
|
| 4054 |
"graph.neural-ode-graph": {
|
| 4055 |
"query": "\"graph neural ODE\" in:description",
|
| 4056 |
"years": [
|
| 4057 |
+
2026,
|
| 4058 |
+
2025
|
| 4059 |
]
|
| 4060 |
},
|
| 4061 |
"graph.persistent-homology": {
|
|
|
|
| 4193 |
"llm.generative-ai": {
|
| 4194 |
"query": "\"generative AI\" in:description",
|
| 4195 |
"years": [
|
| 4196 |
+
2026,
|
| 4197 |
+
2025
|
| 4198 |
]
|
| 4199 |
},
|
| 4200 |
"llm.instruction-tuning": {
|
| 4201 |
"query": "\"instruction tuning\" in:readme",
|
| 4202 |
"years": [
|
| 4203 |
+
2026,
|
| 4204 |
+
2025
|
| 4205 |
]
|
| 4206 |
},
|
| 4207 |
"llm.language-model": {
|
| 4208 |
"query": "\"language model\" in:description",
|
| 4209 |
"years": [
|
| 4210 |
+
2026,
|
| 4211 |
+
2025
|
| 4212 |
]
|
| 4213 |
},
|
| 4214 |
"llm.language-models": {
|
| 4215 |
"query": "topic:large-language-models",
|
| 4216 |
"years": [
|
| 4217 |
+
2026,
|
| 4218 |
+
2025
|
| 4219 |
]
|
| 4220 |
},
|
| 4221 |
"llm.large-language-model": {
|
| 4222 |
"query": "\"large language model\" in:description",
|
| 4223 |
"years": [
|
| 4224 |
+
2026,
|
| 4225 |
+
2025
|
| 4226 |
]
|
| 4227 |
},
|
| 4228 |
"llm.long-context": {
|
| 4229 |
"query": "\"long context\" \"language model\" in:readme",
|
| 4230 |
"years": [
|
| 4231 |
+
2026,
|
| 4232 |
+
2025
|
| 4233 |
]
|
| 4234 |
},
|
| 4235 |
"llm.multimodal": {
|
| 4236 |
"query": "\"multimodal language model\" in:description",
|
| 4237 |
"years": [
|
| 4238 |
+
2026,
|
| 4239 |
+
2025
|
| 4240 |
]
|
| 4241 |
},
|
| 4242 |
"llm.parameter-efficient-finetuning": {
|
| 4243 |
"query": "\"parameter-efficient fine-tuning\" in:readme",
|
| 4244 |
"years": [
|
| 4245 |
+
2026,
|
| 4246 |
+
2025
|
| 4247 |
]
|
| 4248 |
},
|
| 4249 |
"llm.preference-optimization": {
|
| 4250 |
"query": "\"direct preference optimization\" in:readme",
|
| 4251 |
"years": [
|
| 4252 |
+
2026,
|
| 4253 |
+
2025
|
| 4254 |
]
|
| 4255 |
},
|
| 4256 |
"llm.quantization": {
|
| 4257 |
"query": "\"LLM quantization\" in:readme",
|
| 4258 |
"years": [
|
| 4259 |
+
2026,
|
| 4260 |
+
2025
|
| 4261 |
]
|
| 4262 |
},
|
| 4263 |
"llm.speculative-decoding": {
|
| 4264 |
"query": "\"speculative decoding\" in:readme",
|
| 4265 |
"years": [
|
| 4266 |
+
2026,
|
| 4267 |
+
2025
|
| 4268 |
]
|
| 4269 |
},
|
| 4270 |
"llm.synthetic-data": {
|
|
|
|
| 4399 |
"medical.eeg": {
|
| 4400 |
"query": "EEG \"deep learning\" in:description,readme",
|
| 4401 |
"years": [
|
| 4402 |
+
2026,
|
| 4403 |
+
2025
|
| 4404 |
]
|
| 4405 |
},
|
| 4406 |
"medical.ehr": {
|
| 4407 |
"query": "\"electronic health record\" in:readme",
|
| 4408 |
"years": [
|
| 4409 |
+
2026,
|
| 4410 |
+
2025
|
| 4411 |
]
|
| 4412 |
},
|
| 4413 |
"medical.genomics": {
|
| 4414 |
"query": "\"clinical genomics\" in:description,readme",
|
| 4415 |
"years": [
|
| 4416 |
+
2026,
|
| 4417 |
+
2025
|
| 4418 |
]
|
| 4419 |
},
|
| 4420 |
"medical.histopathology": {
|
| 4421 |
"query": "\"histopathology image analysis\" in:readme",
|
| 4422 |
"years": [
|
| 4423 |
+
2026,
|
| 4424 |
+
2025
|
| 4425 |
]
|
| 4426 |
},
|
| 4427 |
"medical.medical-image-reconstruction": {
|
| 4428 |
"query": "\"MRI reconstruction\" in:description,readme",
|
| 4429 |
"years": [
|
| 4430 |
+
2026,
|
| 4431 |
+
2025
|
| 4432 |
]
|
| 4433 |
},
|
| 4434 |
"medical.medical-image-registration": {
|
| 4435 |
"query": "\"medical image registration\" in:description,readme",
|
| 4436 |
"years": [
|
| 4437 |
+
2026,
|
| 4438 |
+
2025
|
| 4439 |
]
|
| 4440 |
},
|
| 4441 |
"medical.medical-image-segmentation": {
|
| 4442 |
"query": "\"medical image segmentation\" in:description",
|
| 4443 |
"years": [
|
| 4444 |
+
2026,
|
| 4445 |
+
2025
|
| 4446 |
]
|
| 4447 |
},
|
| 4448 |
"medical.medical-imaging": {
|
| 4449 |
"query": "\"medical imaging\" in:readme",
|
| 4450 |
"years": [
|
| 4451 |
+
2026,
|
| 4452 |
+
2025
|
| 4453 |
]
|
| 4454 |
},
|
| 4455 |
"medical.medical-language-model": {
|
| 4456 |
"query": "\"medical language model\" in:description",
|
| 4457 |
"years": [
|
| 4458 |
+
2026,
|
| 4459 |
+
2025
|
| 4460 |
]
|
| 4461 |
},
|
| 4462 |
"medical.medical-robotics": {
|
| 4463 |
"query": "\"surgical robotics\" \"machine learning\" in:description,readme",
|
| 4464 |
"years": [
|
| 4465 |
+
2026,
|
| 4466 |
+
2025
|
| 4467 |
]
|
| 4468 |
},
|
| 4469 |
"medical.neural-decoding": {
|
| 4470 |
"query": "\"neural data decoding\" in:description",
|
| 4471 |
"years": [
|
| 4472 |
+
2026,
|
| 4473 |
+
2025
|
| 4474 |
]
|
| 4475 |
},
|
| 4476 |
"medical.neuroimaging": {
|
|
|
|
| 4580 |
"multimodal.image-to-3d": {
|
| 4581 |
"query": "\"image to 3D\" in:readme",
|
| 4582 |
"years": [
|
| 4583 |
+
2026,
|
| 4584 |
+
2025
|
| 4585 |
]
|
| 4586 |
},
|
| 4587 |
"multimodal.image-to-video": {
|
| 4588 |
"query": "\"image to video\" in:readme",
|
| 4589 |
"years": [
|
| 4590 |
+
2026,
|
| 4591 |
+
2025
|
| 4592 |
]
|
| 4593 |
},
|
| 4594 |
"multimodal.motion-generation": {
|
| 4595 |
"query": "\"human motion generation\" in:readme",
|
| 4596 |
"years": [
|
| 4597 |
+
2026,
|
| 4598 |
+
2025
|
| 4599 |
]
|
| 4600 |
},
|
| 4601 |
"multimodal.nerf": {
|
| 4602 |
"query": "topic:nerf",
|
| 4603 |
"years": [
|
| 4604 |
+
2026,
|
| 4605 |
+
2025
|
| 4606 |
]
|
| 4607 |
},
|
| 4608 |
"multimodal.neural-rendering": {
|
| 4609 |
"query": "\"neural rendering\" \"radiance fields\" in:description",
|
| 4610 |
"years": [
|
| 4611 |
+
2026,
|
| 4612 |
+
2025
|
| 4613 |
]
|
| 4614 |
},
|
| 4615 |
"multimodal.point-cloud": {
|
| 4616 |
"query": "\"point cloud\" in:description",
|
| 4617 |
"years": [
|
| 4618 |
+
2026,
|
| 4619 |
+
2025
|
| 4620 |
]
|
| 4621 |
},
|
| 4622 |
"multimodal.scene-understanding": {
|
| 4623 |
"query": "\"scene understanding\" in:description",
|
| 4624 |
"years": [
|
| 4625 |
+
2026,
|
| 4626 |
+
2025
|
| 4627 |
]
|
| 4628 |
},
|
| 4629 |
"multimodal.text-to-3d": {
|
| 4630 |
"query": "\"text to 3D\" in:readme",
|
| 4631 |
"years": [
|
| 4632 |
+
2026,
|
| 4633 |
+
2025
|
| 4634 |
]
|
| 4635 |
},
|
| 4636 |
"multimodal.text-to-image": {
|
| 4637 |
"query": "\"text-to-image\" in:description",
|
| 4638 |
"years": [
|
| 4639 |
+
2026,
|
| 4640 |
+
2025
|
| 4641 |
]
|
| 4642 |
},
|
| 4643 |
"multimodal.text-to-video": {
|
| 4644 |
"query": "\"text-to-video\" in:description",
|
| 4645 |
"years": [
|
| 4646 |
+
2026,
|
| 4647 |
+
2025
|
| 4648 |
]
|
| 4649 |
},
|
| 4650 |
"multimodal.video-language-model": {
|
| 4651 |
"query": "\"video language model\" in:readme",
|
| 4652 |
"years": [
|
| 4653 |
+
2026,
|
| 4654 |
+
2025
|
| 4655 |
]
|
| 4656 |
},
|
| 4657 |
"multimodal.video-question-answering": {
|
|
|
|
| 4798 |
"nlp.named-entity-recognition": {
|
| 4799 |
"query": "\"named entity recognition\" in:readme",
|
| 4800 |
"years": [
|
| 4801 |
+
2026,
|
| 4802 |
+
2025
|
| 4803 |
]
|
| 4804 |
},
|
| 4805 |
"nlp.neural-reranking": {
|
| 4806 |
"query": "\"neural reranking\" in:description",
|
| 4807 |
"years": [
|
| 4808 |
+
2026,
|
| 4809 |
+
2025
|
| 4810 |
]
|
| 4811 |
},
|
| 4812 |
"nlp.question-answering": {
|
| 4813 |
"query": "\"question answering\" in:description",
|
| 4814 |
"years": [
|
| 4815 |
+
2026,
|
| 4816 |
+
2025
|
| 4817 |
]
|
| 4818 |
},
|
| 4819 |
"nlp.rag": {
|
| 4820 |
"query": "\"retrieval augmented generation\" in:description",
|
| 4821 |
"years": [
|
| 4822 |
+
2026,
|
| 4823 |
+
2025
|
| 4824 |
]
|
| 4825 |
},
|
| 4826 |
"nlp.semantic-search": {
|
| 4827 |
"query": "\"semantic search\" in:description",
|
| 4828 |
"years": [
|
| 4829 |
+
2026,
|
| 4830 |
+
2025
|
| 4831 |
]
|
| 4832 |
},
|
| 4833 |
"nlp.sentence-embeddings": {
|
| 4834 |
"query": "\"sentence embeddings\" in:description",
|
| 4835 |
"years": [
|
| 4836 |
+
2026,
|
| 4837 |
+
2025
|
| 4838 |
]
|
| 4839 |
},
|
| 4840 |
"nlp.subword-tokenization": {
|
| 4841 |
"query": "\"subword tokenization\" in:readme",
|
| 4842 |
"years": [
|
| 4843 |
+
2026,
|
| 4844 |
+
2025
|
| 4845 |
]
|
| 4846 |
},
|
| 4847 |
"nlp.text-classification": {
|
| 4848 |
"query": "\"text classification\" in:description",
|
| 4849 |
"years": [
|
| 4850 |
+
2026,
|
| 4851 |
+
2025
|
| 4852 |
]
|
| 4853 |
},
|
| 4854 |
"nlp.text-generation": {
|
| 4855 |
"query": "\"text generation\" in:readme",
|
| 4856 |
"years": [
|
| 4857 |
+
2026,
|
| 4858 |
+
2025
|
| 4859 |
]
|
| 4860 |
},
|
| 4861 |
"nlp.text-summarization": {
|
| 4862 |
"query": "\"text summarization\" in:description",
|
| 4863 |
"years": [
|
| 4864 |
+
2026,
|
| 4865 |
+
2025
|
| 4866 |
]
|
| 4867 |
},
|
| 4868 |
"nlp.topic-modeling": {
|
| 4869 |
"query": "\"topic modeling\" in:readme",
|
| 4870 |
"years": [
|
| 4871 |
+
2026,
|
| 4872 |
+
2025
|
| 4873 |
]
|
| 4874 |
},
|
| 4875 |
"recall.archaeological-remote-sensing": {
|
|
|
|
| 4931 |
"recall.epidemiological-modeling": {
|
| 4932 |
"query": "\"epidemiological modeling\" machine learning in:name,description,readme",
|
| 4933 |
"years": [
|
| 4934 |
+
2026,
|
| 4935 |
+
2025
|
| 4936 |
]
|
| 4937 |
},
|
| 4938 |
"recall.grid-stability-prediction": {
|
| 4939 |
"query": "\"grid stability prediction\" in:name,description,readme",
|
| 4940 |
"years": [
|
| 4941 |
+
2026,
|
| 4942 |
+
2025
|
| 4943 |
]
|
| 4944 |
},
|
| 4945 |
"recall.historical-document-recognition": {
|
| 4946 |
"query": "\"historical document recognition\" in:name,description,readme",
|
| 4947 |
"years": [
|
| 4948 |
+
2026,
|
| 4949 |
+
2025
|
| 4950 |
]
|
| 4951 |
},
|
| 4952 |
"recall.infrastructure-damage-detection": {
|
| 4953 |
"query": "\"infrastructure damage detection\" deep learning in:name,description,readme",
|
| 4954 |
"years": [
|
| 4955 |
+
2026,
|
| 4956 |
+
2025
|
| 4957 |
]
|
| 4958 |
},
|
| 4959 |
"recall.insurance-risk-modeling": {
|
| 4960 |
"query": "\"insurance risk\" machine learning in:name,description,readme",
|
| 4961 |
"years": [
|
| 4962 |
+
2026,
|
| 4963 |
+
2025
|
| 4964 |
]
|
| 4965 |
},
|
| 4966 |
"recall.legal-document-classification": {
|
| 4967 |
"query": "\"legal document classification\" in:name,description,readme",
|
| 4968 |
"years": [
|
| 4969 |
+
2026,
|
| 4970 |
+
2025
|
| 4971 |
]
|
| 4972 |
},
|
| 4973 |
"recall.legal-nlp": {
|
| 4974 |
"query": "legal NLP in:name,description,readme",
|
| 4975 |
"years": [
|
| 4976 |
+
2026,
|
| 4977 |
+
2025
|
| 4978 |
]
|
| 4979 |
},
|
| 4980 |
"recall.name.artificial-intelligence": {
|
| 4981 |
"query": "\"artificial intelligence\" in:name,description,readme",
|
| 4982 |
"years": [
|
| 4983 |
+
2026,
|
| 4984 |
+
2025
|
| 4985 |
]
|
| 4986 |
},
|
| 4987 |
"recall.name.deep-learning": {
|
| 4988 |
"query": "\"deep learning\" in:name,description,readme",
|
| 4989 |
"years": [
|
| 4990 |
+
2026,
|
| 4991 |
+
2025
|
| 4992 |
]
|
| 4993 |
},
|
| 4994 |
"recall.name.diffusion-model": {
|
| 4995 |
"query": "diffusion model in:name,description,readme",
|
| 4996 |
"years": [
|
| 4997 |
+
2026,
|
| 4998 |
+
2025
|
| 4999 |
]
|
| 5000 |
},
|
| 5001 |
"recall.name.foundation-model": {
|
|
|
|
| 5197 |
"rl.hierarchical": {
|
| 5198 |
"query": "\"hierarchical reinforcement learning\" in:description",
|
| 5199 |
"years": [
|
| 5200 |
+
2026,
|
| 5201 |
+
2025
|
| 5202 |
]
|
| 5203 |
},
|
| 5204 |
"rl.imitation-learning": {
|
| 5205 |
"query": "\"imitation learning\" in:description",
|
| 5206 |
"years": [
|
| 5207 |
+
2026,
|
| 5208 |
+
2025
|
| 5209 |
]
|
| 5210 |
},
|
| 5211 |
"rl.inverse": {
|
| 5212 |
"query": "\"inverse reinforcement learning\" in:description",
|
| 5213 |
"years": [
|
| 5214 |
+
2026,
|
| 5215 |
+
2025
|
| 5216 |
]
|
| 5217 |
},
|
| 5218 |
"rl.model-based": {
|
| 5219 |
"query": "\"model-based reinforcement learning\" in:description",
|
| 5220 |
"years": [
|
| 5221 |
+
2026,
|
| 5222 |
+
2025
|
| 5223 |
]
|
| 5224 |
},
|
| 5225 |
"rl.model-free": {
|
| 5226 |
"query": "\"model-free reinforcement learning\" in:description",
|
| 5227 |
"years": [
|
| 5228 |
+
2026,
|
| 5229 |
+
2025
|
| 5230 |
]
|
| 5231 |
},
|
| 5232 |
"rl.multiagent": {
|
| 5233 |
"query": "\"multi-agent reinforcement learning\" in:description",
|
| 5234 |
"years": [
|
| 5235 |
+
2026,
|
| 5236 |
+
2025
|
| 5237 |
]
|
| 5238 |
},
|
| 5239 |
"rl.offline": {
|
| 5240 |
"query": "\"offline reinforcement learning\" in:description",
|
| 5241 |
"years": [
|
| 5242 |
+
2026,
|
| 5243 |
+
2025
|
| 5244 |
]
|
| 5245 |
},
|
| 5246 |
"rl.planning": {
|
| 5247 |
"query": "\"reinforcement learning planning\" in:description",
|
| 5248 |
"years": [
|
| 5249 |
+
2026,
|
| 5250 |
+
2025
|
| 5251 |
]
|
| 5252 |
},
|
| 5253 |
"rl.policy-gradient": {
|
| 5254 |
"query": "\"policy gradient\" in:description",
|
| 5255 |
"years": [
|
| 5256 |
+
2026,
|
| 5257 |
+
2025
|
| 5258 |
]
|
| 5259 |
},
|
| 5260 |
"rl.ppo": {
|
| 5261 |
"query": "\"proximal policy optimization\" in:description",
|
| 5262 |
"years": [
|
| 5263 |
+
2026,
|
| 5264 |
+
2025
|
| 5265 |
]
|
| 5266 |
},
|
| 5267 |
"rl.preference": {
|
|
|
|
| 5347 |
"robotics.manipulation": {
|
| 5348 |
"query": "\"robot manipulation\" in:description",
|
| 5349 |
"years": [
|
| 5350 |
+
2026,
|
| 5351 |
+
2025
|
| 5352 |
]
|
| 5353 |
},
|
| 5354 |
"robotics.navigation": {
|
| 5355 |
"query": "\"robot navigation\" in:description",
|
| 5356 |
"years": [
|
| 5357 |
+
2026,
|
| 5358 |
+
2025
|
| 5359 |
]
|
| 5360 |
},
|
| 5361 |
"robotics.robot-control": {
|
| 5362 |
"query": "\"robot control\" in:description",
|
| 5363 |
"years": [
|
| 5364 |
+
2026,
|
| 5365 |
+
2025
|
| 5366 |
]
|
| 5367 |
},
|
| 5368 |
"robotics.robot-foundation-model": {
|
| 5369 |
"query": "robot foundation model in:description,readme",
|
| 5370 |
"years": [
|
| 5371 |
+
2026,
|
| 5372 |
+
2025
|
| 5373 |
]
|
| 5374 |
},
|
| 5375 |
"robotics.robot-learning": {
|
| 5376 |
"query": "\"robot learning\" in:description",
|
| 5377 |
"years": [
|
| 5378 |
+
2026,
|
| 5379 |
+
2025
|
| 5380 |
]
|
| 5381 |
},
|
| 5382 |
"robotics.robot-manipulation-learning": {
|
| 5383 |
"query": "\"robot manipulation learning\" in:readme",
|
| 5384 |
"years": [
|
| 5385 |
+
2026,
|
| 5386 |
+
2025
|
| 5387 |
]
|
| 5388 |
},
|
| 5389 |
"robotics.robot-motion-planning": {
|
| 5390 |
"query": "\"robot motion planning\" in:description",
|
| 5391 |
"years": [
|
| 5392 |
+
2026,
|
| 5393 |
+
2025
|
| 5394 |
]
|
| 5395 |
},
|
| 5396 |
"robotics.robotics-reinforcement-learning": {
|
| 5397 |
"query": "\"robotics reinforcement learning\" in:description",
|
| 5398 |
"years": [
|
| 5399 |
+
2026,
|
| 5400 |
+
2025
|
| 5401 |
]
|
| 5402 |
},
|
| 5403 |
"robotics.robotics-topic": {
|
| 5404 |
"query": "topic:robotics",
|
| 5405 |
"years": [
|
| 5406 |
+
2026,
|
| 5407 |
+
2025
|
| 5408 |
]
|
| 5409 |
},
|
| 5410 |
"robotics.sim2real": {
|
| 5411 |
"query": "\"sim-to-real\" in:description",
|
| 5412 |
"years": [
|
| 5413 |
+
2026,
|
| 5414 |
+
2025
|
| 5415 |
]
|
| 5416 |
},
|
| 5417 |
"robotics.slam": {
|
|
|
|
| 5503 |
"science.fusion-plasma": {
|
| 5504 |
"query": "fusion plasma in:description \"machine learning\"",
|
| 5505 |
"years": [
|
| 5506 |
+
2026,
|
| 5507 |
+
2025
|
| 5508 |
]
|
| 5509 |
},
|
| 5510 |
"science.gravitational-waves": {
|
| 5511 |
"query": "\"gravitational wave\" \"machine learning\" in:description,readme",
|
| 5512 |
"years": [
|
| 5513 |
+
2026,
|
| 5514 |
+
2025
|
| 5515 |
]
|
| 5516 |
},
|
| 5517 |
"science.inverse-problems": {
|
| 5518 |
"query": "\"inverse problems\" in:description",
|
| 5519 |
"years": [
|
| 5520 |
+
2026,
|
| 5521 |
+
2025
|
| 5522 |
]
|
| 5523 |
},
|
| 5524 |
"science.neural-operators": {
|
| 5525 |
"query": "\"neural operator\" in:description",
|
| 5526 |
"years": [
|
| 5527 |
+
2026,
|
| 5528 |
+
2025
|
| 5529 |
]
|
| 5530 |
},
|
| 5531 |
"science.ocean-modeling": {
|
| 5532 |
"query": "\"ocean modeling\" \"machine learning\" in:description,readme",
|
| 5533 |
"years": [
|
| 5534 |
+
2026,
|
| 5535 |
+
2025
|
| 5536 |
]
|
| 5537 |
},
|
| 5538 |
"science.particle-physics": {
|
| 5539 |
"query": "\"particle physics\" in:description",
|
| 5540 |
"years": [
|
| 5541 |
+
2026,
|
| 5542 |
+
2025
|
| 5543 |
]
|
| 5544 |
},
|
| 5545 |
"science.photonics": {
|
| 5546 |
"query": "photonics \"machine learning\" in:description,readme",
|
| 5547 |
"years": [
|
| 5548 |
+
2026,
|
| 5549 |
+
2025
|
| 5550 |
]
|
| 5551 |
},
|
| 5552 |
"science.physics": {
|
| 5553 |
"query": "physics in:description",
|
| 5554 |
"years": [
|
| 5555 |
+
2026,
|
| 5556 |
+
2025
|
| 5557 |
]
|
| 5558 |
},
|
| 5559 |
"science.physics-informed-neural-networks": {
|
| 5560 |
"query": "\"physics-informed neural network\" in:description",
|
| 5561 |
"years": [
|
| 5562 |
+
2026,
|
| 5563 |
+
2025
|
| 5564 |
]
|
| 5565 |
},
|
| 5566 |
"science.plasma-physics": {
|
| 5567 |
"query": "\"plasma physics\" in:description",
|
| 5568 |
"years": [
|
| 5569 |
+
2026,
|
| 5570 |
+
2025
|
| 5571 |
]
|
| 5572 |
},
|
| 5573 |
"science.quantum-materials": {
|
|
|
|
| 5677 |
"specialized.fmri-decoding-ml": {
|
| 5678 |
"query": "\"fMRI decoding\" \"machine learning\" in:description,readme",
|
| 5679 |
"years": [
|
| 5680 |
+
2026,
|
| 5681 |
+
2025
|
| 5682 |
]
|
| 5683 |
},
|
| 5684 |
"specialized.machine-unlearning": {
|
| 5685 |
"query": "\"machine unlearning\" in:description,readme",
|
| 5686 |
"years": [
|
| 5687 |
+
2026,
|
| 5688 |
+
2025
|
| 5689 |
]
|
| 5690 |
},
|
| 5691 |
"specialized.mechanistic-interpretability": {
|
| 5692 |
"query": "\"mechanistic interpretability\" in:description,readme",
|
| 5693 |
"years": [
|
| 5694 |
+
2026,
|
| 5695 |
+
2025
|
| 5696 |
]
|
| 5697 |
},
|
| 5698 |
"specialized.medical-image-registration-deep-learning": {
|
| 5699 |
"query": "\"medical image registration\" \"deep learning\" in:description,readme",
|
| 5700 |
"years": [
|
| 5701 |
+
2026,
|
| 5702 |
+
2025
|
| 5703 |
]
|
| 5704 |
},
|
| 5705 |
"specialized.pathology-foundation-model": {
|
| 5706 |
"query": "\"pathology foundation model\" \"machine learning\" in:description,readme",
|
| 5707 |
"years": [
|
| 5708 |
+
2026,
|
| 5709 |
+
2025
|
| 5710 |
]
|
| 5711 |
},
|
| 5712 |
"specialized.spiking-neural-network": {
|
| 5713 |
"query": "\"spiking neural network\" in:description,readme",
|
| 5714 |
"years": [
|
| 5715 |
+
2026,
|
| 5716 |
+
2025
|
| 5717 |
]
|
| 5718 |
},
|
| 5719 |
"specialized.test-time-adaptation": {
|
| 5720 |
"query": "\"test-time adaptation\" in:description,readme",
|
| 5721 |
"years": [
|
| 5722 |
+
2026,
|
| 5723 |
+
2025
|
| 5724 |
]
|
| 5725 |
},
|
| 5726 |
"timeseries.anomaly-detection": {
|
|
|
|
| 5782 |
"timeseries.long-horizon": {
|
| 5783 |
"query": "\"long horizon forecasting\" in:readme",
|
| 5784 |
"years": [
|
| 5785 |
+
2026,
|
| 5786 |
+
2025
|
| 5787 |
]
|
| 5788 |
},
|
| 5789 |
"timeseries.multivariate": {
|
| 5790 |
"query": "\"multivariate time series\" in:description",
|
| 5791 |
"years": [
|
| 5792 |
+
2026,
|
| 5793 |
+
2025
|
| 5794 |
]
|
| 5795 |
},
|
| 5796 |
"timeseries.nbeats": {
|
| 5797 |
"query": "N-BEATS in:description",
|
| 5798 |
"years": [
|
| 5799 |
+
2026,
|
| 5800 |
+
2025
|
| 5801 |
]
|
| 5802 |
},
|
| 5803 |
"timeseries.patchtst": {
|
| 5804 |
"query": "PatchTST in:description",
|
| 5805 |
"years": [
|
| 5806 |
+
2026,
|
| 5807 |
+
2025
|
| 5808 |
]
|
| 5809 |
},
|
| 5810 |
"timeseries.predictive-maintenance": {
|
| 5811 |
"query": "\"predictive maintenance\" in:description",
|
| 5812 |
"years": [
|
| 5813 |
+
2026,
|
| 5814 |
+
2025
|
| 5815 |
]
|
| 5816 |
},
|
| 5817 |
"timeseries.probabilistic-forecasting": {
|
| 5818 |
"query": "\"probabilistic forecasting\" in:readme",
|
| 5819 |
"years": [
|
| 5820 |
+
2026,
|
| 5821 |
+
2025
|
| 5822 |
]
|
| 5823 |
},
|
| 5824 |
"timeseries.remaining-useful-life": {
|
| 5825 |
"query": "\"remaining useful life\" in:readme",
|
| 5826 |
"years": [
|
| 5827 |
+
2026,
|
| 5828 |
+
2025
|
| 5829 |
]
|
| 5830 |
},
|
| 5831 |
"timeseries.sensor-data": {
|
| 5832 |
"query": "\"sensor time series\" in:description",
|
| 5833 |
"years": [
|
| 5834 |
+
2026,
|
| 5835 |
+
2025
|
| 5836 |
]
|
| 5837 |
},
|
| 5838 |
"timeseries.state-space-models": {
|
| 5839 |
"query": "\"state space model\" in:description",
|
| 5840 |
"years": [
|
| 5841 |
+
2026,
|
| 5842 |
+
2025
|
| 5843 |
]
|
| 5844 |
},
|
| 5845 |
"timeseries.streaming": {
|
| 5846 |
"query": "\"streaming time series\" in:readme",
|
| 5847 |
"years": [
|
| 5848 |
+
2026,
|
| 5849 |
+
2025
|
| 5850 |
]
|
| 5851 |
},
|
| 5852 |
"timeseries.synthetic-generation": {
|
|
|
|
| 5949 |
"trust.causal-mediation": {
|
| 5950 |
"query": "\"causal mediation analysis\" in:description",
|
| 5951 |
"years": [
|
| 5952 |
+
2026,
|
| 5953 |
+
2025
|
| 5954 |
]
|
| 5955 |
},
|
| 5956 |
"trust.causal-ml": {
|
| 5957 |
"query": "\"causal machine learning\" in:description",
|
| 5958 |
"years": [
|
| 5959 |
+
2026,
|
| 5960 |
+
2025
|
| 5961 |
]
|
| 5962 |
},
|
| 5963 |
"trust.causal-representation-learning": {
|
| 5964 |
"query": "\"causal representation learning\" in:description",
|
| 5965 |
"years": [
|
| 5966 |
+
2026,
|
| 5967 |
+
2025
|
| 5968 |
]
|
| 5969 |
},
|
| 5970 |
"trust.conformal-prediction": {
|
| 5971 |
"query": "\"conformal prediction\" in:description",
|
| 5972 |
"years": [
|
| 5973 |
+
2026,
|
| 5974 |
+
2025
|
| 5975 |
]
|
| 5976 |
},
|
| 5977 |
"trust.counterfactual-explanations": {
|
| 5978 |
"query": "\"counterfactual explanation\" in:description",
|
| 5979 |
"years": [
|
| 5980 |
+
2026,
|
| 5981 |
+
2025
|
| 5982 |
]
|
| 5983 |
},
|
| 5984 |
"trust.differential-privacy": {
|
| 5985 |
"query": "\"differential privacy\" in:description",
|
| 5986 |
"years": [
|
| 5987 |
+
2026,
|
| 5988 |
+
2025
|
| 5989 |
]
|
| 5990 |
},
|
| 5991 |
"trust.distribution-shift": {
|
| 5992 |
"query": "\"distribution shift\" in:description",
|
| 5993 |
"years": [
|
| 5994 |
+
2026,
|
| 5995 |
+
2025
|
| 5996 |
]
|
| 5997 |
},
|
| 5998 |
"trust.domain-generalization": {
|
| 5999 |
"query": "\"domain generalization\" in:description",
|
| 6000 |
"years": [
|
| 6001 |
+
2026,
|
| 6002 |
+
2025
|
| 6003 |
]
|
| 6004 |
},
|
| 6005 |
"trust.explainable-ai": {
|
| 6006 |
"query": "\"explainable AI\" in:description",
|
| 6007 |
"years": [
|
| 6008 |
+
2026,
|
| 6009 |
+
2025
|
| 6010 |
]
|
| 6011 |
},
|
| 6012 |
"trust.federated-learning": {
|
| 6013 |
"query": "\"federated learning\" in:description",
|
| 6014 |
"years": [
|
| 6015 |
+
2026,
|
| 6016 |
+
2025
|
| 6017 |
]
|
| 6018 |
},
|
| 6019 |
"trust.instrumental-variable-ml": {
|
| 6020 |
"query": "\"double machine learning\" in:description",
|
| 6021 |
"years": [
|
| 6022 |
+
2026,
|
| 6023 |
+
2025
|
| 6024 |
]
|
| 6025 |
},
|
| 6026 |
"trust.interpretable-ml": {
|
|
|
|
| 6141 |
"vision.image-restoration": {
|
| 6142 |
"query": "\"image restoration\" in:readme",
|
| 6143 |
"years": [
|
| 6144 |
+
2026,
|
| 6145 |
+
2025
|
| 6146 |
]
|
| 6147 |
},
|
| 6148 |
"vision.image-retrieval": {
|
| 6149 |
"query": "\"image retrieval\" in:readme",
|
| 6150 |
"years": [
|
| 6151 |
+
2026,
|
| 6152 |
+
2025
|
| 6153 |
]
|
| 6154 |
},
|
| 6155 |
"vision.image-super-resolution": {
|
| 6156 |
"query": "\"image super-resolution\" in:readme",
|
| 6157 |
"years": [
|
| 6158 |
+
2026,
|
| 6159 |
+
2025
|
| 6160 |
]
|
| 6161 |
},
|
| 6162 |
"vision.image-to-image-translation": {
|
| 6163 |
"query": "\"image-to-image translation\" in:readme",
|
| 6164 |
"years": [
|
| 6165 |
+
2026,
|
| 6166 |
+
2025
|
| 6167 |
]
|
| 6168 |
},
|
| 6169 |
"vision.neural-rendering": {
|
| 6170 |
"query": "\"neural rendering\" in:description",
|
| 6171 |
"years": [
|
| 6172 |
+
2026,
|
| 6173 |
+
2025
|
| 6174 |
]
|
| 6175 |
},
|
| 6176 |
"vision.object-detection": {
|
| 6177 |
"query": "\"object detection\" in:description",
|
| 6178 |
"years": [
|
| 6179 |
+
2026,
|
| 6180 |
+
2025
|
| 6181 |
]
|
| 6182 |
},
|
| 6183 |
"vision.object-tracking": {
|
| 6184 |
"query": "\"object tracking\" in:readme",
|
| 6185 |
"years": [
|
| 6186 |
+
2026,
|
| 6187 |
+
2025
|
| 6188 |
]
|
| 6189 |
},
|
| 6190 |
"vision.ocr": {
|
| 6191 |
"query": "topic:ocr",
|
| 6192 |
"years": [
|
| 6193 |
+
2026,
|
| 6194 |
+
2025
|
| 6195 |
]
|
| 6196 |
},
|
| 6197 |
"vision.open-vocabulary-detection": {
|
| 6198 |
"query": "\"open-vocabulary detection\" in:readme",
|
| 6199 |
"years": [
|
| 6200 |
+
2026,
|
| 6201 |
+
2025
|
| 6202 |
]
|
| 6203 |
},
|
| 6204 |
"vision.optical-flow": {
|
| 6205 |
"query": "topic:optical-flow",
|
| 6206 |
"years": [
|
| 6207 |
+
2026,
|
| 6208 |
+
2025
|
| 6209 |
]
|
| 6210 |
},
|
| 6211 |
"vision.pose-estimation": {
|
| 6212 |
"query": "\"human pose estimation\" in:readme",
|
| 6213 |
"years": [
|
| 6214 |
+
2026,
|
| 6215 |
+
2025
|
| 6216 |
]
|
| 6217 |
},
|
| 6218 |
"vision.promptable-segmentation": {
|
|
|
|
| 6279 |
"end": "2026-09-24",
|
| 6280 |
"search_policy_version": 2,
|
| 6281 |
"start_year": 2008,
|
| 6282 |
+
"updated_at": "2026-09-28T18:33:08Z"
|
| 6283 |
}
|