5 papers · 1 filter
THG-Omni: Traceable Human-Centric Graph Supervision for Video Reasoning
Jisheng Dang, Kai Wei, Ronghao Lin +6
Omni-modal models can answer questions about video, but their predictions rarely show which participant, event, or interval supports an answer. Moreover, answer-level supervision a…
Multi-Agent Self-Improving Reinforcement Learning for Video Reasoning
Mingwen Zhang, Jisheng Dang, Minqiang Yang +3
Video reasoning tasks such as grounded video question answering and temporal grounding require selecting temporal evidence that supports the query. In many current training setups,…
A Robust Point Cloud Analysis Framework Inspired By Primary Visual Cortex
Jisheng Dang, Dengyue Pan, Delin Deng +6
Despite significant advancements in point cloud analysis, reducing energy consumption and improving robustness remain understudied, largely due to the inherent limitations of Convo…
Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder
Dang Jisheng, Wu Xudong, Wang Bimei +7
Existing video segmenter and grounder approaches, exemplified by Sa2VA, directly fuse features within segmentation models. This often results in an undesirable entanglement of dyna…
MUPA: Towards Multi-Path Agentic Reasoning for Grounded Video Question Answering
Jisheng Dang, Huilin Song, Junbin Xiao +6
Grounded Video Question Answering (Grounded VideoQA) requires aligning textual answers with explicit visual evidence. However, modern multimodal models often rely on linguistic pri…