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Models/Neural Content Planning + conditional copy

Neural Content Planning + conditional copy

Reported on 6 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Adversarial3 results

  • Text GenerationonRotoWire (Relation Generation)
    count· 2018-09-03
    34.28
    best: 46.7 (SeqPlan)
    SOTA
    Data-to-Text Generation with Content Selection and PlanningarXiv:1809.00582
  • Text GenerationonRotoWire (Content Ordering)
    BLEU· 2018-09-03
    16.5
    best: 17.5 (Hierarchical Transformer Encoder + conditional copy)
    SOTA
    Data-to-Text Generation with Content Selection and PlanningarXiv:1809.00582
  • Text GenerationonRotoWire
    BLEU· 2018-09-03
    16.5
    best: 17.96 (HierarchicalEncoder + NR + IR)
    SOTA
    Data-to-Text Generation with Content Selection and PlanningarXiv:1809.00582

Natural Language Processing3 results

  • Data-to-Text GenerationonRotoWire (Relation Generation)
    count· 2018-09-03
    34.28
    best: 46.7 (SeqPlan)
    SOTA
    Data-to-Text Generation with Content Selection and PlanningarXiv:1809.00582
  • Data-to-Text GenerationonRotoWire (Content Ordering)
    BLEU· 2018-09-03
    16.5
    best: 17.5 (Hierarchical Transformer Encoder + conditional copy)
    SOTA
    Data-to-Text Generation with Content Selection and PlanningarXiv:1809.00582
  • Data-to-Text GenerationonRotoWire
    BLEU· 2018-09-03
    16.5
    best: 17.96 (HierarchicalEncoder + NR + IR)
    SOTA
    Data-to-Text Generation with Content Selection and PlanningarXiv:1809.00582