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L. Zheng

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#artificial intelligence Preprint Sep 2026

Beyond Accuracy: How Procedural Traces Shift the Decision Criterion of LLM Overseers

Organizations increasingly use oversight loops where one large language model (LLM) audits another's outputs alongside procedural traces of claimed steps. A common concern about such LLM-as-a-judge pipelines is that detailed traces make overseers gullible. Using signal detection theory, we audit five LLM overseers on 1...

Zi-Han Chen, Di Zhu, L. Zheng et al. · 0 citations
Review Jul 2026

When Synthetic Users Fail: A Cross-Domain Benchmark of LLM-Simulated Human Survey Responses

The cross-domain benchmark and the evaluation framework for intelligent synthetic-user evidence is made available on request, so that teams can determine in advance when synthetic-user evidence is safe for decision support and when it is not.

Zihang Chen, Di Zhu, L. Zheng · 2 citations

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