1 citations · 1 across the 5 of their papers we have counts for
7 papers
Differential Privacy Protected Preference Alignment on Survey Derived Data
Xiuyuan Qi, Yi Wang, Wenjie Wang
Preference alignment enables language models to better reflect human values, but the preference data contains sensitive information, especially when derived from surveys about poli…
GPO-V: Jailbreak Diffusion Vision Language Model by Global Probability Optimization
Yu Pan, Andi Zhang, Yi Wang +2
Diffusion Vision-Language Models (dVLMs), built upon the non-causal foundations of Diffusion Large Language Models (dLLMs), have demonstrated remarkable efficacy in multimodal task…
From Individuals to Interactions: Benchmarking Gender Bias in Multimodal Large Language Models from the Lens of Social Relationship
Yue Xu, Wenjie Wang
Ensuring the trustworthiness of Multimodal Large Language Models (MLLMs) requires rigorous evaluation of gender bias, particularly in socially sensitive domains. Existing benchmark…
DR.GAP: Mitigating Bias in Large Language Models using Gender-Aware Prompting with Decoupled Reasoning
Hongye Qiu, Yue Xu, Yi Wang +2
Large Language Models (LLMs) exhibit strong natural language understanding capabilities but also inherit and amplify societal biases, particularly gender bias, raising fairness con…
Auto-Search and Refinement: An Automated Framework for Gender Bias Mitigation in Large Language Models
Yue Xu, Chengyan Fu, Li Xiong +2
Pre-training large language models (LLMs) on vast text corpora enhances natural language processing capabilities but risks encoding social biases, particularly gender bias. While p…
: A Comprehensive Study on Jailbreak Attacks and Defenses for Multimodal Large Language Models
Fenghua Weng, Yue Xu, Chengyan Fu +1
As deep learning advances, Large Language Models (LLMs) and their multimodal counterparts, Multimodal Large Language Models (MLLMs), have shown exceptional performance in many real…
Cross-modality Information Check for Detecting Jailbreaking in Multimodal Large Language Models
Yue Xu, Xiuyuan Qi, Zhan Qin +1
Multimodal Large Language Models (MLLMs) extend the capacity of LLMs to understand multimodal information comprehensively, achieving remarkable performance in many vision-centric t…