TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/DAM

DAM

Reported on 26 benchmarks across 3 tasks · 1 paper

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

Natural Language Processing26 results

  • Recognizing Emotion Cause in ConversationsonRECCON
    Macro F1· 2022-10-26
    78.73
    best: 81.25 (KEC)
    Discourse-Aware Emotion Cause Extraction in ConversationsarXiv:2210.14419
  • Recognizing Emotion Cause in ConversationsonRECCON
    Neg. F1· 2022-10-26
    89.55
    best: 97.69 (Window transformer)
    Discourse-Aware Emotion Cause Extraction in ConversationsarXiv:2210.14419
  • Recognizing Emotion Cause in ConversationsonRECCON
    Pos. F1· 2022-10-26
    67.91
    best: 71.18 (MPEG)
    Discourse-Aware Emotion Cause Extraction in ConversationsarXiv:2210.14419
  • Visual Question Answering (VQA)onGQA Test2019
    Accuracy
    59.72
    best: 89.3 (human)
  • Visual Question Answering (VQA)onGQA Test2019
    Binary
    77.97
    best: 91.2 (human)
  • Visual Question Answering (VQA)onGQA Test2019
    Consistency
    89.43
    best: 98.4 (human)
  • Visual Question Answering (VQA)onGQA Test2019
    Distribution
    6.25
    best: 93.08 (GlobalPrior)
  • Visual Question Answering (VQA)onGQA Test2019
    Open
    43.61
    best: 87.4 (human)
  • Visual Question Answering (VQA)onGQA Test2019
    Plausibility
    84.89
    best: 97.2 (human)
  • Visual Question Answering (VQA)onGQA Test2019
    Validity
    96.55
    best: 98.9 (human)
  • Conversational Response SelectiononDouban
    MAP
    0.55
    best: 0.651 (SEMSOL(W/o utterances))
  • Conversational Response SelectiononDouban
    MRR
    0.601
    best: 0.688 (Uni-Enc+BERT-FP)
  • Conversational Response SelectiononDouban
    P@1
    0.427
    best: 0.518 (Uni-Enc+BERT-FP)
  • Conversational Response SelectiononDouban
    R10@1
    0.254
    best: 0.33 (SEMSOL)
  • Conversational Response SelectiononDouban
    R10@2
    0.41
    best: 0.557 (Uni-Enc+BERT-FP)
  • Conversational Response SelectiononDouban
    R10@5
    0.757
    best: 0.877 (SEMSOL(W/o utterances))
  • Conversational Response SelectiononRRS
    MAP
    0.511
    best: 0.702 (BERT-FP)
  • Conversational Response SelectiononRRS
    MRR
    0.534
    best: 0.715 (SA-BERT+BERT-FP)
  • Conversational Response SelectiononRRS
    P@1
    0.347
    best: 0.555 (SA-BERT+BERT-FP)
  • Conversational Response SelectiononRRS
    R10@1
    0.308
    best: 0.497 (SA-BERT+BERT-FP)
  • Conversational Response SelectiononRRS
    R10@2
    0.457
    best: 0.708 (BERT-FP)
  • Conversational Response SelectiononRRS
    R10@5
    0.751
    best: 0.931 (SA-BERT+BERT-FP)
  • Conversational Response SelectiononUbuntu Dialogue (v1, Ranking)
    R10@1
    0.767
    best: 0.918 (Dial-MAE)
  • Conversational Response SelectiononUbuntu Dialogue (v1, Ranking)
    R10@2
    0.874
    best: 0.965 (BERT-FP+EDHNS)
  • Conversational Response SelectiononUbuntu Dialogue (v1, Ranking)
    R10@5
    0.969
    best: 0.994 (BERT-FP+EDHNS)
  • Conversational Response SelectiononUbuntu Dialogue (v1, Ranking)
    R2@1
    0.938
    best: 0.975 (BERT-SL)