Papers with end-to-end refinement approaches

1 papers
Learning to Refine with Fine-Grained Natural Language Feedback (2024.findings-emnlp)

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Challenge: Recent work has explored the capability of large language models to identify and correct errors in LLM-generated responses.
Approach: They propose to combine refinement with feedback into three distinct competencies . step 1: Detect, Critique, Refine gives a fine-grained feedback about errors .
Outcome: The proposed method outperforms existing refinement approaches and models not fine-tuned for factuality critiquing.

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