Showing 2025Show all
3 papers · 1 filter
cs.CV2025
Towards Effective Long Video Understanding of Multimodal Large Language Models via One-shot Clip Retrieval
Tao Chen, Shaobo Ju, Qiong Wu +6
Due to excessive memory overhead, most Multimodal Large Language Models (MLLMs) can only process videos of limited frames. In this paper, we propose an effective and efficient para…
cs.CV2025
Grounded Chain-of-Thought for Multimodal Large Language Models
Qiong Wu, Xiangcong Yang, Yiyi Zhou +4
Despite great progress, existing multimodal large language models (MLLMs) are prone to visual hallucination, greatly impeding their trustworthy applications. In this paper, we stud…
cs.CV2025
What Kind of Visual Tokens Do We Need? Training-free Visual Token Pruning for Multi-modal Large Language Models from the Perspective of Graph
Yutao Jiang, Qiong Wu, Wenhao Lin +2
Recent Multimodal Large Language Models(MLLMs) often use a large number of visual tokens to compensate their visual shortcoming, leading to excessive computation and obvious visual…