Author

Shuang-Jie Yao

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#artificial intelligence Preprint Oct 2026

Cost-Efficient Theorem Proving via Agent Orchestration in Program Verification

Program verification establishes software correctness through machine-checkable proofs constructed in theorem provers. It's a guarantee especially valuable for code generated by large language models (LLMs), which is fluent but carries no assurance of correctness. Almost all existing provers, however, pursue pass rates...

Shuang-Jie Yao, Nikolaus Holzer, Mark Santolucito et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Similarity Is Not Validity: Defending LLM Semantic Caches Against Poisoning

This work proposes a novel defense that recovers necessary information needed to distinguish valid from invalid cache hits from the raw text of the cache key, and proves that Deletion Gain stays positive when a deletion leaves text close enough to the rewrite, and searches for such deletions with a sliding window.

Zi-Han Zhang, Shuang-Jie Yao, Ze-Sen Liu et al. · 0 citations