Improving LLMs via Validator-to-Generator Alignment
Researchers propose a new alignment method to bridge the generator-validator gap in LLMs.
LLMs often exhibit inconsistency where they generate content they later deem invalid. This work introduces a principled correction method to align validators with generators, improving output reliability and reducing self-contradiction in model responses.