Rewindable Auto-regressive INference (RAIN)
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Shows that unaligned LLMs can produce aligned responses at inference time via self-evaluation and rewinding.
No fine-tuning needed: Produces human-preference-aligned responses from unaligned base LLMs without any additional fine-tuning.
Self-evaluation: The LLM evaluates its own in-progress generation against alignment criteria, flagging problematic paths.
Rewind mechanism: When self-evaluation detects a problematic direction, the model rewinds and regenerates - an inference-time search strategy.
Practical alignment: Offers a lightweight alignment pattern for cases where fine-tuning isn't feasible (e.g., API-only models or rapid policy iteration).
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