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Models/S_1^R

S_1^R

Reported on 10 benchmarks across 2 tasks · 1 paper · 10 SOTA

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

Adversarial5 results

  • Text GenerationonE2E NLG Challenge
    BLEU· 2019-04-02
    68.6
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301
  • Text GenerationonE2E NLG Challenge
    CIDEr· 2019-04-02
    2.37
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301
  • Text GenerationonE2E NLG Challenge
    METEOR· 2019-04-02
    45.25
    best: 46.11 (Self-memory)
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301
  • Text GenerationonE2E NLG Challenge
    NIST· 2019-04-02
    8.73
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301
  • Text GenerationonE2E NLG Challenge
    ROUGE-L· 2019-04-02
    70.82
    best: 70.83 (Zhang)
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301

Natural Language Processing5 results

  • Data-to-Text GenerationonE2E NLG Challenge
    BLEU· 2019-04-02
    68.6
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301
  • Data-to-Text GenerationonE2E NLG Challenge
    CIDEr· 2019-04-02
    2.37
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301
  • Data-to-Text GenerationonE2E NLG Challenge
    METEOR· 2019-04-02
    45.25
    best: 46.11 (Self-memory)
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301
  • Data-to-Text GenerationonE2E NLG Challenge
    NIST· 2019-04-02
    8.73
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301
  • Data-to-Text GenerationonE2E NLG Challenge
    ROUGE-L· 2019-04-02
    70.82
    best: 70.83 (Zhang)
    SOTA
    Pragmatically Informative Text GenerationarXiv:1904.01301