LEATHER: A Framework for Learning to Generate Human-like Text in Dialogue (2022.findings-aacl)
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| Challenge: | Generating coherent, human-like text for dialogue remains a challenge . lack of careful design of rewards can lead to mode-collapse in dialogue . |
| Approach: | They propose a theoretical framework for learning to generate text in dialogue . they propose to use data-shift to develop theoretical guarantees for learners . |
| Outcome: | The proposed framework improves both task-success and human-likeness of the generated text. |
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