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Xuhan Huang

3 accepted papers

2026

CALM Before the STORM: Unlocking Native Reasoning for Optimization Modeling

ICML 2026poster

Large Reasoning Models (LRMs) have demonstrated strong capabilities in complex multi-step reasoning, opening new opportunities for automating optimization modeling. However, existing domain adaptation methods, originally designed for earlier instruction-tuned models, often fail to exploit the advanc…

Cited by 0SourceScholar
2026

VeriEquivBench: An Equivalence Score for Ground-Truth-Free Evaluation of Formally Verifiable Code

ICLR 2026poster

Formal verification is the next frontier for ensuring the correctness of code generated by Large Language Models (LLMs). While methods that co-generate code and formal specifications in formal languages, like Dafny, can, in principle, prove alignment with user intent, progress is bottlenecked by sp…

Cited by 0SourcecodeScholar