collaborators

6 papers

cs.CL2026

Learning from the Self-future: On-policy Self-distillation for dLLMs

Yifu Luo, Zeyu Chen, Haoyu Wang +4

On-policy self-distillation (OPSD) has proven effective for post-training large language models (LLMs), yet its application to diffusion LLMs (dLLMs) remains unexplored. Existing O…

cs.CV2026

Principled RL for Flow Matching Emerges from the Chunk-level Policy Optimization

Yifu Luo, Haoyuan Sun, Xinhao Hu +12

Recent Progress in post-training flow matching for text-to-image (T2I) generation with Group Relative Policy Optimization (GRPO) has demonstrated strong potential. However, it is h…

cs.RO2026

Exploring Bottlenecks in VLM-LLM Navigation: How 3D Scene Understanding Capability Impacts Zero-Shot VLN

Ziyi Xia, Chaoran Xiong, Litao Wei +2

Zero-shot vision-and-language navigation (VLN) has gained significant attention due to its minimal data collection costs and inherent generalization. This paradigm is typically dri…

cs.CV2026

Enhancing Domain Generalization in 3D Human Pose Estimation through Controllable Generative Augmentation

Xinhao Hu, Yiyi Zhang, Liqing Zhang +1

Pedestrian motion, due to its causal nature, is strongly influenced by domain gaps arising from discrepancies between training and testing data distributions. Focusing on 3D human…

cs.RO2026

SFCo-Nav: Efficient Zero-Shot Visual Language Navigation via Collaboration of Slow LLM and Fast Attributed Graph Alignment

Chaoran Xiong, Litao Wei, Xinhao Hu +5

Recent advances in large vision-language models (VLMs) and large language models (LLMs) have enabled zero-shot approaches to visual language navigation (VLN), where an agent follow…

cs.CV2026

Reinforcement Learning Meets Masked Generative Models: Mask-GRPO for Text-to-Image Generation

Yifu Luo, Xinhao Hu, Keyu Fan +6

Reinforcement learning (RL) has garnered increasing attention in text-to-image (T2I) generation. However, most existing RL approaches are tailored to either diffusion models or aut…