Zihan Xiao — accepted AI-conference papers

2026

TimeViper: A Hybrid Mamba-Transformer Vision-Language Model for Efficient Long Video Understanding

Boshen Xu, Zihan Xiao, Jiaze Li, Jianzhong Ju, Zhenbo Luo, Jian Luan +1

CVPR 2026

We introduce TimeViper, a hybrid vision-language model designed to tackle challenges of long video understanding. Processing long videos demands both an efficient model architecture and an effective mechanism for handling extended temporal contexts. To this end, TimeViper adopts a hybrid Mamba-Trans

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2025

Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding

Ye Wang, Ziheng Wang, Boshen Xu, Yang Du, Kejun Lin, Zihan Xiao +11

NeurIPS 2025poster

Temporal Video Grounding (TVG), the task of locating specific video segments based on language queries, is a core challenge in long-form video understanding. While recent Large Vision-Language Models (LVLMs) have shown early promise in tackling TVG through supervised fine-tuning (SFT), their ability…

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