6 papers
SafeSteer: A Decoding-level Defense Mechanism for Multimodal Large Language Models
Xinyi Zeng, Xue Yang, Jingyuan Zhang +5
Multimodal large language models (MLLMs) are gaining increasing attention. Due to the heterogeneity of their input features, they face significant challenges in terms of jailbreak…
DPN-LE: Dual Personality Neuron Localization and Editing for Large Language Models
Lifan Zheng, Xue Yang, Jiawei Chen +6
With the widespread adoption of large language models (LLMs), understanding their personality representation mechanisms has become critical. As a novel paradigm in Personality Edit…
Me-Agent: A Personalized Mobile Agent with Two-Level User Habit Learning for Enhanced Interaction
Shuoxin Wang, Chang Liu, Gowen Loo +5
Large Language Model (LLM)-based mobile agents have made significant performance advancements. However, these agents often follow explicit user instructions while overlooking perso…
Rethinking the Reliability of Multi-agent System: A Perspective from Byzantine Fault Tolerance
Lifan Zheng, Jiawei Chen, Qinghong Yin +3
Ensuring the reliability of agent architectures and effectively identifying problematic agents when failures occur are crucial challenges in multi-agent systems (MAS). Advances in…
MobileRAG: Enhancing Mobile Agent with Retrieval-Augmented Generation
Gowen Loo, Chang Liu, Qinghong Yin +4
Smartphones have become indispensable in people's daily lives, permeating nearly every aspect of modern society. With the continuous advancement of large language models (LLMs), nu…
From Pixels to Tokens: Revisiting Object Hallucinations in Large Vision-Language Models
Yuying Shang, Xinyi Zeng, Yutao Zhu +6
Hallucinations in large vision-language models (LVLMs) are a significant challenge, i.e., generating objects that are not presented in the visual input, which impairs their reliabi…