task_path stringlengths 3 199 ⌀ | dataset stringlengths 1 128 ⌀ | model_name stringlengths 1 223 ⌀ | paper_url stringlengths 21 601 ⌀ | metric_name stringlengths 1 50 ⌀ | metric_value stringlengths 1 9.22k ⌀ |
|---|---|---|---|---|---|
Unconditional Crystal Generation | MP20 | FlowMM | https://arxiv.org/abs/2406.04713v1 | Validity | 80.30 |
Unconditional Crystal Generation | MP20 | FlowMM | https://arxiv.org/abs/2406.04713v1 | DFT Stable, Unique, Novel Rate | 2.8 |
Drug ATC Classification | ATC-GRAPH | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Aiming | 0.9694 |
Drug ATC Classification | ATC-GRAPH | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Coverage | 0.9688 |
Drug ATC Classification | ATC-GRAPH | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Accuracy | 0.9614 |
Drug ATC Classification | ATC-GRAPH | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Absolute True | 0.9456 |
Drug ATC Classification | ATC-GRAPH | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Absolute False | 0.0057 |
Drug ATC Classification | ATC-GRAPH | ATC-CNN | https://doi.org/10.1093/bib/bbaf194 | Aiming | 0.7734 |
Drug ATC Classification | ATC-GRAPH | ATC-CNN | https://doi.org/10.1093/bib/bbaf194 | Coverage | 0.7642 |
Drug ATC Classification | ATC-GRAPH | ATC-CNN | https://doi.org/10.1093/bib/bbaf194 | Accuracy | 0.7563 |
Drug ATC Classification | ATC-GRAPH | ATC-CNN | https://doi.org/10.1093/bib/bbaf194 | Absolute True | 0.7311 |
Drug ATC Classification | ATC-GRAPH | ATC-CNN | https://doi.org/10.1093/bib/bbaf194 | Absolute False | 0.0355 |
Drug ATC Classification | ATC-SMILES | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Aiming | 0.9608 |
Drug ATC Classification | ATC-SMILES | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Coverage | 0.9609 |
Drug ATC Classification | ATC-SMILES | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Accuracy | 0.9542 |
Drug ATC Classification | ATC-SMILES | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Absolute True | 0.9397 |
Drug ATC Classification | ATC-SMILES | GraphATC | https://doi.org/10.1093/bib/bbaf194 | Absolute False | 0.0068 |
Drug ATC Classification | ATC-SMILES | ATC-CNN | https://doi.org/10.1093/bib/bbac346 | Aiming | 0.9583 |
Drug ATC Classification | ATC-SMILES | ATC-CNN | https://doi.org/10.1093/bib/bbac346 | Coverage | 0.9414 |
Drug ATC Classification | ATC-SMILES | ATC-CNN | https://doi.org/10.1093/bib/bbac346 | Accuracy | 0.9399 |
Drug ATC Classification | ATC-SMILES | ATC-CNN | https://doi.org/10.1093/bib/bbac346 | Absolute True | 0.9177 |
Drug ATC Classification | ATC-SMILES | ATC-CNN | https://doi.org/10.1093/bib/bbac346 | Absolute False | 0.0094 |
Nested Term Recognition > Nested Term Recognition from Flat Supervision | RuTermEval (Track 3) | lemm. inc. + early dmg | https://arxiv.org/abs/2504.16007v2 | Scoreboard Weighted F1 | 0.4547 |
Nested Term Recognition > Nested Term Recognition from Flat Supervision | RuTermEval (Track 3) | lemm. inc. + early dmg | https://arxiv.org/abs/2504.16007v2 | Scoreboard Class-agnostic F1 | 0.5875 |
Nested Term Recognition > Nested Term Recognition from Flat Supervision | RuTermEval (Track 1) | lemm. inc. + early dmg | https://arxiv.org/abs/2504.16007v2 | Scoreboard F1 | 0.7281 |
Nested Term Recognition > Nested Term Recognition from Flat Supervision | RuTermEval (Track 2) | lemm. inc. + early dmg | https://arxiv.org/abs/2504.16007v2 | Scoreboard Weighted F1 | 0.631 |
Nested Term Recognition > Nested Term Recognition from Flat Supervision | RuTermEval (Track 2) | lemm. inc. + early dmg | https://arxiv.org/abs/2504.16007v2 | Scoreboard Class-agnostic F1 | 0.7337 |
3D Generation | E.T. the Exceptional Trajectories | DIRECTOR C | https://arxiv.org/abs/2407.01516v1 | FD_ClaTr | 3.76 |
3D Generation | E.T. the Exceptional Trajectories | DIRECTOR C | https://arxiv.org/abs/2407.01516v1 | ClaTr-Score | 21.95 |
3D Generation | E.T. the Exceptional Trajectories | DIRECTOR C | https://arxiv.org/abs/2407.01516v1 | Classifier-F1 | 0.48 |
3D Generation | E.T. the Exceptional Trajectories | DIRECTOR A | https://arxiv.org/abs/2407.01516v1 | FD_ClaTr | 3.88 |
3D Generation | E.T. the Exceptional Trajectories | DIRECTOR A | https://arxiv.org/abs/2407.01516v1 | ClaTr-Score | 20.76 |
3D Generation | E.T. the Exceptional Trajectories | DIRECTOR A | https://arxiv.org/abs/2407.01516v1 | Classifier-F1 | 0.42 |
3D Generation | E.T. the Exceptional Trajectories | DIRECTOR B | https://arxiv.org/abs/2407.01516v1 | FD_ClaTr | 6.10 |
3D Generation | E.T. the Exceptional Trajectories | DIRECTOR B | https://arxiv.org/abs/2407.01516v1 | ClaTr-Score | 20.78 |
3D Generation | E.T. the Exceptional Trajectories | DIRECTOR B | https://arxiv.org/abs/2407.01516v1 | Classifier-F1 | 0.39 |
3D Generation | E.T. the Exceptional Trajectories | MDM | https://arxiv.org/abs/2209.14916v2 | FD_ClaTr | 6.79 |
3D Generation | E.T. the Exceptional Trajectories | MDM | https://arxiv.org/abs/2209.14916v2 | ClaTr-Score | 18.32 |
3D Generation | E.T. the Exceptional Trajectories | MDM | https://arxiv.org/abs/2209.14916v2 | Classifier-F1 | 0.34 |
TinyQA Benchmark++ | tinyqabenchmark_core-en | gemma-3-4b | https://arxiv.org/abs/2505.12058v1 | Exact Match | 86.5 |
TinyQA Benchmark++ | tinyqabenchmark_core-en | mistral-24b-instruct | https://arxiv.org/abs/2505.12058v1 | Exact Match | 84.6 |
TinyQA Benchmark++ | tinyqabenchmark_core-en | llama-3.2-3b-instruct | https://arxiv.org/abs/2505.12058v1 | Exact Match | 84.6 |
TinyQA Benchmark++ | tinyqabenchmark_core-en | ministral-8b | https://arxiv.org/abs/2505.12058v1 | Exact Match | 80.8 |
TinyQA Benchmark++ | tinyqabenchmark_core-en | ministral-3b | https://arxiv.org/abs/2505.12058v1 | Exact Match | 76.9 |
TinyQA Benchmark++ | tinyqabenchmark_core-en | llama-3.2-1b-instruct | https://arxiv.org/abs/2505.12058v1 | Exact Match | 53.8 |
TinyQA Benchmark++ | tinyqabenchmark_core-en | mistral-7b-instruct | https://arxiv.org/abs/2505.12058v1 | Exact Match | 50.0 |
TinyQA Benchmark++ | tinyqabenchmark_core-en | gemma-3-12b | https://arxiv.org/abs/2505.12058v1 | Exact Macth | 90.4 |
Weakly-supervised Temporal Action Localization | UCF101-24 | Structured Keypoint Pooling | https://arxiv.org/abs/2303.15270v1 | mAP@0.2 | 61.8 |
Weakly-supervised Temporal Action Localization | ActivityNet-1.3 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.5 | 41.0 |
Weakly-supervised Temporal Action Localization | ActivityNet-1.3 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.75 | 24.9 |
Weakly-supervised Temporal Action Localization | ActivityNet-1.3 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.95 | 6.2 |
Weakly-supervised Temporal Action Localization | ActivityNet-1.3 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP | 25.1 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP IOU@0.1 | 70.1 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP IOU@0.2 | 63.6 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP IOU@0.3 | 54.5 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP IOU@0.4 | 45.7 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP IOU@0.5 | 38.3 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP IOU@0.6 | 26.4 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP IOU@0.7 | 13.4 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP IOU@0.8 | 6.9 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP IOU@0.9 | 2.0 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589v1 | mAP@AVG(0.1:0.9) | 35.7 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589#:~:text=Cross%2Dmodal%20Consensus%20Network%20for%20Weakly%20Supervised%20Temporal%20Action%20Localization,-Fa%2DTing%20Hong&text=Weakly%20supervised%20temporal%20action%20localization%20(WS%2DTAL)%20is%20a,with%20video%2Dlevel%20categorical%20supervision. | mAP IOU@0.5 | 38.3 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | CO2-Net | https://arxiv.org/abs/2107.12589#:~:text=Cross%2Dmodal%20Consensus%20Network%20for%20Weakly%20Supervised%20Temporal%20Action%20Localization,-Fa%2DTing%20Hong&text=Weakly%20supervised%20temporal%20action%20localization%20(WS%2DTAL)%20is%20a,with%20video%2Dlevel%20categorical%20supervision. | mAP@AVG(0.1:0.9) | 35.7 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP IOU@0.1 | 61.2 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP IOU@0.2 | 56.1 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP IOU@0.3 | 48.1 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP IOU@0.4 | 39.0 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP IOU@0.5 | 30.1 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP IOU@0.6 | 19.2 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP IOU@0.7 | 10.6 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP IOU@0.8 | 4.8 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP IOU@0.9 | 1.0 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | A2CL-PT | https://arxiv.org/abs/2007.06643v1 | mAP@AVG(0.1:0.9) | 30.0 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.1 | 71.2 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.2 | 65.5 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.3 | 57.1 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.4 | 46.8 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.5 | 36.6 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.6 | 25.2 |
Weakly-supervised Temporal Action Localization | THUMOS’14 | ASM-Loc | https://arxiv.org/abs/2203.15187v1 | mAP IOU@0.7 | 13.4 |
Audio-visual Question Answering | MUSIC-AVQA | VAST | https://arxiv.org/abs/2305.18500v2 | Acc | 80.7 |
Audio-visual Question Answering | MUSIC-AVQA | CoQo(Internvideo2) | null | Acc | 79.6 |
Audio-visual Question Answering | MUSIC-AVQA | VALOR | https://arxiv.org/abs/2304.08345v2 | Acc | 78.9 |
Audio-visual Question Answering | MUSIC-AVQA | CAD | https://arxiv.org/abs/2310.16754v2 | Acc | 78.26 |
Audio-visual Question Answering | MUSIC-AVQA | LAVISH | https://arxiv.org/abs/2212.07983v2 | Acc | 77.08 |
Audio-visual Question Answering | MUSIC-AVQA | ST-AVQA | https://arxiv.org/abs/2203.14072v2 | Acc | 71.52 |
Audio-visual Question Answering > AUDIO-VISUAL QUESTION ANSWERING (MUSIC-AVQA-v2.0) | MUSIC-AVQA v2.0 | Meerkat | https://arxiv.org/abs/2407.01851v2 | Accuracy | 79.15 |
Audio-visual Question Answering > AUDIO-VISUAL QUESTION ANSWERING (MUSIC-AVQA-v2.0) | MUSIC-AVQA v2.0 | QA-TIGER | https://arxiv.org/abs/2503.04459v1 | Accuracy | 76.43 |
Audio-visual Question Answering > AUDIO-VISUAL QUESTION ANSWERING (MUSIC-AVQA-v2.0) | MUSIC-AVQA v2.0 | LAST-Att | https://arxiv.org/abs/2310.06238v1 | Accuracy | 75.44 |
Audio-visual Question Answering > AUDIO-VISUAL QUESTION ANSWERING (MUSIC-AVQA-v2.0) | MUSIC-AVQA v2.0 | LAVISH | https://arxiv.org/abs/2212.07983v2 | Accuracy | 73.18 |
Audio-visual Question Answering > AUDIO-VISUAL QUESTION ANSWERING (MUSIC-AVQA-v2.0) | MUSIC-AVQA v2.0 | AVST | https://arxiv.org/abs/2203.14072v2 | Accuracy | 71.02 |
Anomaly Classification | VisA | APRIL-GAN | https://arxiv.org/abs/2305.17382v3 | Detection AUROC | 78.0 |
Anomaly Classification | MVTecAD | VELM | https://arxiv.org/abs/2505.02626v1 | Accuracy (% ) | 81.4 |
Anomaly Classification | MVTecAD | Echo | https://arxiv.org/abs/2501.15795v1 | Accuracy (% ) | 72.9 |
Anomaly Classification | MVTec-AC | VELM | https://arxiv.org/abs/2505.02626v1 | Accuracy (% ) | 84.0 |
Anomaly Classification | VisA-AC | VELM | https://arxiv.org/abs/2505.02626v1 | Accuracy(%) | 69.6 |
Anomaly Classification | GoodsAD | PatchCore-100% | https://arxiv.org/abs/2106.08265v2 | AUROC | 85.5 |
Anomaly Classification | GoodsAD | PatchCore-100% | https://arxiv.org/abs/2106.08265v2 | AUPR | 86.1 |
Anomaly Classification | GoodsAD | PatchCore-1% | https://arxiv.org/abs/2106.08265v2 | AUROC | 81.4 |
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