Youtube
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| LF Mislabeling Identification | Youtube | AP94.9 | 32 | |
| Synthetic Network Generation | YouTube | GFDL1 Score7.97 | 29 | |
| End model evaluation | Youtube | Test Loss0.229 | 22 | |
| Link Prediction | YouTube | ROC AUC92.51 | 21 | |
| Sentiment Analysis | YouTube (test) | A3 Score54.2 | 15 | |
| Synthetic Network Generation | YouTube | Eigenvalue MMD0.38 | 14 | |
| Classification | Youtube (test) | Test Loss0.215 | 13 | |
| Pronoun Coreference Resolution | YouTube (test) | Accuracy73 | 12 | |
| Speaking Target Identification | YouTube v1.0 (test) | Accuracy74.5 | 12 | |
| Mentioned Player Prediction | YouTube (test) | Accuracy0.625 | 12 | |
| Human Motion Segmentation | YouTube | Accuracy99.74 | 11 | |
| Synthetic Network Generation | YouTube | Link Prediction Accuracy Ratio100 | 10 | |
| Graph Clustering | Youtube | NMI52.7 | 10 | |
| Speech Recognition | YouTube (test) | WER7.5 | 10 | |
| Node Embedding | YouTube | Time (s)57.1 | 10 | |
| Multi-label classification | YouTube (10% train) | Micro-F10.4643 | 10 | |
| Multi-label classification | YouTube (1% train ratio) | Micro-F140.2 | 10 | |
| Multi-party Multi-modal Social Interaction (MMSI) | YouTube | STI Accuracy64.9 | 9 | |
| node classification | YouTube (10% labeled nodes) | Micro F1 Score45.86 | 9 | |
| Whataboutism detection | YouTube (TQ+T) | Precision (W)72 | 8 | |
| Community Detection | Youtube | F1-Score0.327 | 8 | |
| Recommender System Evaluation | YouTube | User Clicks127.113 | 7 | |
| Automatic Speech Recognition | YouTube | WER14.05 | 7 | |
| Cover Song Identification | Youtube | MAP91.7 | 7 | |
| Local Clustering | com-youtube | Operations Needed57,000 | 6 |
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