1 citations · 1 across the 5 of their papers we have counts for
4 papers · 1 filter
Youtu-Parsing-Omni: One Encoder, One Schema, All Modalities
Yunhang Shen, Zhangquan Chen, Xiaotian Li +27
We present Youtu-Parsing-Omni, an omni-modal parser that converts documents, images, audio, and video into structured records grounded in space and time, providing a perception lay…
LOCUS: Local Visual Cue Search for Enhancing Fine-Grained Perception in Multimodal Large Language Models
Zhou Tao, Fang Zhang, Zewen Ding +5
Multimodal Large Language Models (MLLMs) remain unreliable on fine-grained visual perception, even when high-resolution inputs preserve the necessary local details. We identify thi…
Dynamic Token Compression for Efficient Video Understanding through Reinforcement Learning
Shida Wang, YongXiang Hua, Zhou Tao +2
Multimodal Large Language Models have demonstrated remarkable capabilities in video understanding, yet face prohibitive computational costs and performance degradation from ''conte…
DiG: Differential Grounding for Enhancing Fine-Grained Perception in Multimodal Large Language Model
Zhou Tao, Shida Wang, Yongxiang Hua +2
Multimodal Large Language Models have achieved impressive performance on a variety of vision-language tasks, yet their fine-grained visual perception and precise spatial reasoning…