Papers by Zhihui Zhu

2 papers
DivScore: Zero-Shot Detection of LLM-Generated Text in Specialized Domains (2025.emnlp-main)

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Challenge: Existing zero-shot detectors fail when applied to specialized content due to domain shift . DivScore outperforms state-of-the-art detectors in specialized domains .
Approach: They propose a zero-shot detection framework that uses normalized entropy-based scoring and domain knowledge distillation to identify LLM-generated text in specialized domains.
Outcome: The proposed framework outperforms state-of-the-art detectors on medical and legal datasets with 14.4% higher AUROC and 64.0% higher recall.
MolSafeEval: A Benchmark for Uncovering Safety Risks in AI-Generated Molecules (2026.findings-acl)

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Challenge: generative models may produce molecules with toxic, reactive, or otherwise hazardous characteristics.
Approach: They propose a benchmark to evaluate and analyze the safety risks of molecular generation.
Outcome: The proposed benchmark aims to evaluate and analyze the safety risks of molecular generation.

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