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Models/DUA

DUA

Reported on 12 benchmarks across 1 task · 1 paper · 12 SOTA

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

Natural Language Processing12 results

  • Conversational Response SelectiononDouban
    MAP· 2018-06-24
    0.551
    best: 0.651 (SEMSOL(W/o utterances))
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononDouban
    MRR· 2018-06-24
    0.599
    best: 0.688 (Uni-Enc+BERT-FP)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononDouban
    P@1· 2018-06-24
    0.421
    best: 0.518 (Uni-Enc+BERT-FP)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononDouban
    R10@1· 2018-06-24
    0.243
    best: 0.33 (SEMSOL)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononDouban
    R10@2· 2018-06-24
    0.421
    best: 0.557 (Uni-Enc+BERT-FP)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononDouban
    R10@5· 2018-06-24
    0.78
    best: 0.877 (SEMSOL(W/o utterances))
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononUbuntu Dialogue (v1, Ranking)
    R10@1· 2018-06-24
    0.752
    best: 0.918 (Dial-MAE)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononUbuntu Dialogue (v1, Ranking)
    R10@2· 2018-06-24
    0.868
    best: 0.965 (BERT-FP+EDHNS)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononUbuntu Dialogue (v1, Ranking)
    R10@5· 2018-06-24
    0.962
    best: 0.994 (BERT-FP+EDHNS)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononE-commerce
    R10@1· 2018-06-24
    0.501
    best: 0.957 (BERT-FP+EDHNS)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononE-commerce
    R10@2· 2018-06-24
    0.7
    best: 0.986 (BERT-FP+EDHNS)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102
  • Conversational Response SelectiononE-commerce
    R10@5· 2018-06-24
    0.921
    best: 0.997 (BERT-FP+EDHNS)
    SOTA
    Modeling Multi-turn Conversation with Deep Utterance AggregationarXiv:1806.09102