Jintao Fang — accepted AI-conference papers

2026

Multi-level Causal LLM-based Text-to-Motion Generation with Human Alignment

Xiaodong Chen, Qian Bao, Xudong Liu, Jianping Fang, Jintao Fang, Yongdong Zhang +2

CVPR 2026

Although progress has been made in LLM-based text-driven motion generation, it still has the limitations of generating fine-grained and semantically consistent motions. These limitations stem from: 1) fine-grained motion quantization errors; 2) mismatches between causal reasoning language and non-ca

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2025

Glance2Gaze: Efficient Vision-Language Models from Glance Fusion to Gaze Compression

Juan Chen, Honglin liu, Yingying Ao, Ting Zhang, Yan Huang, Xudong Liu +2

NeurIPS 2025poster

Vision-language models heavily rely on visual representations, yet ensuring its efficiency remains a critical challenge. Most existing approaches focus on reducing visual tokens either at the visual encoder phase or during the LLM decoder stage. Inspired by human visual cognition, where an initial g…

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