7 papers
PICACO: Pluralistic In-Context Value Alignment of LLMs via Total Correlation Optimization
Han Jiang, Dongyao Zhu, Xiaoyuan Yi +3
In-Context Learning has shown great potential for aligning Large Language Models (LLMs) with human values, helping reduce harmful outputs and accommodate diverse preferences withou…
Degrading Voice: A Comprehensive Overview of Robust Voice Conversion Through Input Manipulation
Xining Song, Zhihua Wei, Rui Wang +3
Identity, accent, style, and emotions are essential components of human speech. Voice conversion (VC) techniques process the speech signals of two input speakers and other modaliti…
DAMRO: Dive into the Attention Mechanism of LVLM to Reduce Object Hallucination
Xuan Gong, Tianshi Ming, Xinpeng Wang +1
Despite the great success of Large Vision-Language Models (LVLMs), they inevitably suffer from hallucination. As we know, both the visual encoder and the Large Language Model (LLM)…
Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing
Han Jiang, Xiaoyuan Yi, Zhihua Wei +3
Warning: Contains harmful model outputs. Despite significant advancements, the propensity of Large Language Models (LLMs) to generate harmful and unethical content poses critical c…
MMUnlearner: Reformulating Multimodal Machine Unlearning in the Era of Multimodal Large Language Models
Jiahao Huo, Yibo Yan, Xu Zheng +4
Recent progress in Machine Unlearning (MU) has introduced solutions for the selective removal of private or sensitive information encoded within deep neural networks. Nonetheless,…
DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification
Yu Li, Han Jiang, Zhihua Wei
With the widespread adoption of Large Language Models (LLMs), jailbreak attacks have become an increasingly pressing safety concern. While safety-aligned LLMs can effectively defen…