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Chengyan Fu

2 accepted papers

2025

Auto-Search and Refinement: An Automated Framework for Gender Bias Mitigation in Large Language Models

NeurIPS 2025poster

Pre-training large language models (LLMs) on vast text corpora enhances natural language processing capabilities but risks encoding social biases, particularly gender bias. While parameter-modification methods like fine-tuning mitigate bias, they are resource-intensive, unsuitable for closed-source…

Cited by 0SourceScholar
2025

MMJ-Bench: A Comprehensive Study on Jailbreak Attacks and Defenses for Vision Language Models

AAAI 2025technical

As deep learning advances, Large Language Models (LLMs) and their multimodal counterparts, Vision-Language Models (VLMs), have shown exceptional performance in many real-world tasks. However, VLMs face significant security challenges, such as jailbreak attacks, where attackers attempt to bypass the…