Papers by Yanping Chen
Forget the Unneeded: Backdooring Large Language Models via Contrastive-enhanced Machine Unlearning (2025.findings-emnlp)
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| Challenge: | Existing methods for prompt tuning for Large Language Models find backdoor attacks to be significant in data-rich scenarios. |
| Approach: | They propose a backdoor attacks through contrastive-enhanced machine unlearning in data-limited scenarios . they use a machine un learning method to capture precise backdoor patterns . |
| Outcome: | The proposed method captures precise backdoor patterns without association between triggers and backdoors, reducing side effects. |
Exclusion of Thought: Mitigating Cognitive Load in Large Language Models for Enhanced Reasoning in Multiple-Choice Tasks (2025.acl-long)
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| Challenge: | Multiple-choice questions (MCQs) are widely used and vital assessment format for evaluating large language models (LLMs). |
| Approach: | They propose a reasoning prompt strategy that redirects the model's attention away from erroneous options and eliminates incorrect options. |
| Outcome: | The proposed reasoning prompt reduces cognitive load by steering the model’s attention away from erroneous options, enabling the model to focus more effectively on reasonable answers. |