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Models/DialogXL

DialogXL

Reported on 7 benchmarks across 1 task · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Audio7 results

  • Emotion RecognitiononCPED
    Accuracy of Sentiment· 2020-12-16
    51.24
    best: 51.5 (BERT+AVG+MLP)
    SOTA
    DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionarXiv:2012.08695
  • Emotion RecognitiononCPED
    Macro-F1 of Sentiment· 2020-12-16
    46.96
    best: 48.02 (BERT+AVG+MLP)
    SOTA
    DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionarXiv:2012.08695
  • Emotion RecognitiononIEMOCAP
    Accuracy· 2020-12-16
    66.3
    best: 73.95 (SDT)
    SOTA
    DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionarXiv:2012.08695
  • Emotion RecognitiononIEMOCAP
    Weighted-F1· 2020-12-16
    66.2
    best: 74.08 (SDT)
    SOTA
    DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionarXiv:2012.08695
  • Emotion RecognitiononEmoryNLP
    Weighted-F1· 2020-12-16
    34.73
    best: 42.08 (CKERC)
    DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionarXiv:2012.08695
  • Emotion RecognitiononMELD
    Weighted-F1· 2020-12-16
    62.41
    best: 69.9 (ELR-GNN)
    DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionarXiv:2012.08695
  • Emotion RecognitiononDailyDialog
    Micro-F1· 2020-12-16
    54.93
    best: 64.07 (S+PAGE)
    DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionarXiv:2012.08695