3 papers
cs.CV2026
Towards Fast and Effective Long Video Understanding of Multimodal Large Language Models via Adaptive Quasi-Gaussian Sampling
Kun Zhang, Chenxin Fang, Tao Chen +4
Long video understanding remains a daunting challenge for Multimodal Large Language Models (MLLMs) due to the excessive computation and memory footprint. Thus, keyframe selection i…
cs.CV2026
Scaling the Long Video Understanding of Multimodal Large Language Models via Visual Memory Mechanism
Tao Chen, Kun Zhang, Qiong Wu +5
Long video understanding is a key challenge that plagues the advancement of \emph{Multimodal Large language Models} (MLLMs). In this paper, we study this problem from the perspecti…
cs.IR2025
Composed Multi-modal Retrieval: A Survey of Approaches and Applications
Kun Zhang, Jingyu Li, Zhe Li +10
The burgeoning volume of multi-modal data necessitates advanced retrieval paradigms beyond unimodal and cross-modal approaches. Composed Multi-modal Retrieval (CMR) emerges as a pi…