3 papers
cs.CV2025
Taming Hallucinations: Boosting MLLMs' Video Understanding via Counterfactual Video Generation
Zhe Huang, Hao Wen, Aiming Hao +6
Multimodal Large Language Models (MLLMs) have made remarkable progress in video understanding. However, they suffer from a critical vulnerability: an over-reliance on language prio…
cs.CL2025
Towards Contamination Resistant Benchmarks
Rahmatullah Musawi, Sheng Lu
The rapid development of large language models (LLMs) has transformed the landscape of natural language processing. Evaluating LLMs properly is crucial for understanding their pote…
cs.CL2025
Identifying Aspects in Peer Reviews
Sheng Lu, Ilia Kuznetsov, Iryna Gurevych
Peer review is central to academic publishing, but the growing volume of submissions is straining the process. This motivates the development of computational approaches to support…