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cs.LG2026
Decompose, Structure, and Repair: A Neuro-Symbolic Framework for Autoformalization via Operator Trees
Xiaoyang Liu, Zineng Dong, Yifan Bai +3
Statement autoformalization acts as a critical bridge between human mathematics and formal mathematics by translating natural language problems into formal language. While prior wo…
cs.LG2026
VeriScale: Adversarial Test-Suite Scaling for Verifiable Code Generation
Yifan Bai, Xiaoyang Liu, Zihao Mou +7
As large language models (LLMs) are increasingly deployed for software engineering, constructing high-quality benchmarks is crucial for evaluating not just the functional correctne…
cs.LG2024★ 1 cited
Vision-Language Models Can Self-Improve Reasoning via Reflection
Kanzhi Cheng, Yantao Li, Fangzhi Xu +3
Chain-of-thought (CoT) has proven to improve the reasoning capability of large language models (LLMs). However, due to the complexity of multimodal scenarios and the difficulty in…