2 papers
cs.AI2026
QMAVIS: Long Video-Audio Understanding using Fusion of Large Multimodal Models
Zixing Lin, Jiale Wang, Gee Wah Ng +4
Large Multimodal Models (LMMs) for video-audio understanding have traditionally been evaluated only on shorter videos of a few minutes long. In this paper, we introduce QMAVIS (Q T…
cs.CL2025
Long Context Scaling: Divide and Conquer via Multi-Agent Question-driven Collaboration
Sibo Xiao, Zixin Lin, Wenyang Gao +2
Processing long contexts has become a critical capability for modern large language models (LLMs). Existing works leverage agent-based divide-and-conquer methods for processing lon…