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arXiv · 2301.00355

Second Thoughts are Best: Learning to Re-Align With Human Values from Text Edits

Ruibo Liu·Chenyan Jia·Ge Zhang·Ziyu Zhuang·Tony X Liu·Soroush Vosoughi
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Abstract

We present Second Thought, a new learning paradigm that enables language models (LMs) to re-align with human values. By modeling the chain-of-edits between value-unaligned and value-aligned text, with LM fine-tuning and additional refinement through reinforcement learning, Second Thought not only achieves superior performance in three value alignment benchmark datasets but also shows strong human-value transfer learning ability in few-shot scenarios. The generated editing steps also offer better interpretability and ease for interactive error correction. Extensive human evaluations further confirm its effectiveness.

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Ruibo Liu, Chenyan Jia, Ge Zhang, Ziyu Zhuang, Tony X Liu, Soroush Vosoughi. 2023-01-01. Second Thoughts are Best: Learning to Re-Align With Human Values from Text Edits. https://arxiv.org/abs/2301.00355

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