7 citations · 15 across the 18 of their papers we have counts for
4 papers · 1 filter
Judge Before Answer: Can MLLM Discern the False Premise in Question?
Jidong Li, Lingyong Fang, Haodong Zhao +2
Multimodal large language models (MLLMs) have witnessed astonishing advancements in recent years. Despite these successes, MLLMs remain vulnerable to flase premise problems. Howeve…
Thinking in a Crowd: How Auxiliary Information Shapes LLM Reasoning
Haodong Zhao, Chenyan Zhao, Yansi Li +2
The capacity of Large Language Models (LLMs) to reason is fundamental to their application in complex, knowledge-intensive domains. In real-world scenarios, LLMs are often augmente…
Flooding Spread of Manipulated Knowledge in LLM-Based Multi-Agent Communities
Tianjie Ju, Yiting Wang, Xinbei Ma +7
The rapid adoption of large language models (LLMs) in multi-agent systems has highlighted their impressive capabilities in various applications, such as collaborative problem-solvi…
UOR: Universal Backdoor Attacks on Pre-trained Language Models
Wei Du, Peixuan Li, Boqun Li +2
Backdoors implanted in pre-trained language models (PLMs) can be transferred to various downstream tasks, which exposes a severe security threat. However, most existing backdoor at…