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Zhen Duan

2 accepted papers

2025

Forget the Unneeded: Backdooring Large Language Models via Contrastive-enhanced Machine Unlearning

EMNLP 2025

Prompt tuning for Large Language Models (LLMs) is vulnerable to backdoor attacks. Existing methods find backdoor attacks to be a significant threat in data-rich scenarios. However, in data-limited scenarios, these methods have difficulty capturing precise backdoor patterns, leading to weakened backd

2025

Triples as the Key: Structuring Makes Decomposition and Verification Easier in LLM-based TableQA

ICLR 2025poster

As the mainstream approach, LLMs have been widely applied and researched in TableQA tasks. Currently, the core of LLM-based TableQA methods typically include three phases: question decomposition, sub-question TableQA reasoning, and answer verification. However, several challenges remain in this proc…

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