3 papers
cs.CL2024
LLM Critics Help Catch Bugs in Mathematics: Towards a Better Mathematical Verifier with Natural Language Feedback
Bofei Gao, Zefan Cai, Runxin Xu +10
In recent progress, mathematical verifiers have achieved success in mathematical reasoning tasks by validating the correctness of solutions generated by policy models. However, exi…
cs.CL2024
Synthesizing Text-to-SQL Data from Weak and Strong LLMs
Jiaxi Yang, Binyuan Hui, Min Yang +3
The capability gap between open-source and closed-source large language models (LLMs) remains a challenge in text-to-SQL tasks. In this paper, we introduce a synthetic data approac…
cs.CL2024
Can Large Language Models Always Solve Easy Problems if They Can Solve Harder Ones?
Zhe Yang, Yichang Zhang, Tianyu Liu +4
Large language models (LLMs) have demonstrated impressive capabilities, but still suffer from inconsistency issues (e.g. LLMs can react differently to disturbances like rephrasing…