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Controllable neural story generation via reinforcement learning

· 2018 · arXiv 1809.10736

2 Pith papers cite this work. Polarity classification is still indexing.

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cs.CL 2

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2020 1 2019 1

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Learning to summarize from human feedback

cs.CL · 2020-09-02 · conditional · novelty 7.0

Reinforcement learning on a reward model trained from human summary comparisons produces summaries humans prefer over supervised fine-tuning or human references on TL;DR and transfers to CNN/DM.

Fine-Tuning Language Models from Human Preferences

cs.CL · 2019-09-18 · unverdicted · novelty 7.0

Language models fine-tuned via RL on 5k-60k human preference comparisons produce stylistically better text continuations and human-preferred summaries that sometimes copy input sentences.

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Showing 2 of 2 citing papers.

  • Learning to summarize from human feedback cs.CL · 2020-09-02 · conditional · none · ref 61

    Reinforcement learning on a reward model trained from human summary comparisons produces summaries humans prefer over supervised fine-tuning or human references on TL;DR and transfers to CNN/DM.

  • Fine-Tuning Language Models from Human Preferences cs.CL · 2019-09-18 · unverdicted · none · ref 27

    Language models fine-tuned via RL on 5k-60k human preference comparisons produce stylistically better text continuations and human-preferred summaries that sometimes copy input sentences.