Conversation Disentanglement On Irc
Métriques
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P
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Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | 1-1 | F | P | R | VI | Paper Title | Repository |
|---|---|---|---|---|---|---|---|
| FF ensemble: Intersect | 26.6 | 32.1 | 67.0 | 21.1 | 69.3 | A Large-Scale Corpus for Conversation Disentanglement | |
| Linear | 51.4 | 15.5 | 12.1 | 21.5 | 82.1 | You Talking to Me? A Corpus and Algorithm for Conversation Disentanglement | - |
| Feedforward | 75.6 | 36.2 | 34.6 | 38.0 | 91.3 | A Large-Scale Corpus for Conversation Disentanglement | |
| BERT + BiLSTM | - | 46.8 | 44.3 | 49.6 | 93.3 | Pre-Trained and Attention-Based Neural Networks for Building Noetic Task-Oriented Dialogue Systems | - |
| FF ensemble: Vote | 76.0 | 38.0 | 36.3 | 39.7 | 91.5 | A Large-Scale Corpus for Conversation Disentanglement |
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