Papers with synthetic natural language critiques

1 papers
Improving Reward Models with Synthetic Critiques (2025.findings-naacl)

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Challenge: a recent study shows that reward models overfit on superficial features, hindering generalization performance . prevailing approach to training preference-based reward models presents several challenges .
Approach: They propose a method that uses synthetic natural language critiques to provide additional feedback to large language models.
Outcome: The proposed approach improves performance and data efficiency of RMs initialized from different pretrained models, reducing the reliance on costly human annotations.

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