5 papers
VERHallu: Evaluating and Mitigating Event Relation Hallucination in Video Large Language Models
Zefan Zhang, Kehua Zhu, Shijie Jiang +3
Video Large Language Models (VideoLLMs) exhibit various types of hallucinations. Existing research has primarily focused on hallucinations involving the presence of events, objects…
Stephanie2: Thinking, Waiting, and Making Decisions Like Humans in Step-by-Step AI Social Chat
Hao Yang, Hongyuan Lu, Dingkang Yang +8
Instant-messaging human social chat typically progresses through a sequence of short messages. Existing step-by-step AI chatting systems typically split a one-shot generation into…
From Abstract to Contextual: What LLMs Still Cannot Do in Mathematics
Bowen Cao, Dongdong Zhang, Yixia Li +8
Large language models now solve many benchmark math problems at near-expert levels, yet this progress has not fully translated into reliable performance in real-world applications.…
LNE-Blocking: An Efficient Framework for Contamination Mitigation Evaluation on Large Language Models
Ruijie Hou, Yueyang Jiao, Hanxu Hu +4
The problem of data contamination is now almost inevitable during the development of large language models (LLMs), with the training data commonly integrating those evaluation benc…
Clean Evaluations on Contaminated Visual Language Models
Hongyuan Lu, Shujie Miao, Wai Lam
How to evaluate large language models (LLMs) cleanly has been established as an important research era to genuinely report the performance of possibly contaminated LLMs. Yet, how t…