publications

2026

1. CoRL

   

   Sim-and-Human Co-training for Data-Efficient and Scene-Generalizable Bimanual Manipulation

   Kaipeng Fang, Weiqing Liang, Yuyang Li, Ji Zhang, Pengpeng Zeng, Heng Tao Shen, Jingkuan Song, and Lianli Gao

   In 10th Annual Conference on Robot Learning (CoRL), 2026

   arXiv Bib Website

   @inproceedings{fang2026simhum,
     title = {Sim-and-Human Co-training for Data-Efficient and Scene-Generalizable Bimanual Manipulation},
     author = {Fang, Kaipeng and Liang, Weiqing and Li, Yuyang and Zhang, Ji and Zeng, Pengpeng and Shen, Heng Tao and Song, Jingkuan and Gao, Lianli},
     booktitle = {10th Annual Conference on Robot Learning (CoRL)},
     year = {2026},
   }

2024

1. CVPR

   

   ProS: Prompting-to-simulate Generalized knowledge for Universal Cross-Domain Retrieval

   Kaipeng Fang, Jingkuan Song, Lianli Gao, Pengpeng Zeng, Zhi-Qi Cheng, Xiyao Li, and Heng Tao Shen

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

   TL;DR arXiv Bib Code

   

   This paper proposes Prompting-to-Simulate (ProS), a novel prompt tuning framework for Universal Cross-Domain Retrieval (UCDR) that generates Content-aware Dynamic Prompts via a two-stage simulation process to effectively address domain and semantic shifts, achieving state-of-the-art performance with high parameter efficiency.

   @inproceedings{fang2024pros,
     title = {ProS: Prompting-to-simulate Generalized knowledge for Universal Cross-Domain Retrieval},
     author = {Fang, Kaipeng and Song, Jingkuan and Gao, Lianli and Zeng, Pengpeng and Cheng, Zhi-Qi and Li, Xiyao and Shen, Heng Tao},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
     year = {2024},
     tldr = {This paper proposes Prompting-to-Simulate (ProS), a novel prompt tuning framework for Universal Cross-Domain Retrieval (UCDR) that generates Content-aware Dynamic Prompts via a two-stage simulation process to effectively address domain and semantic shifts, achieving state-of-the-art performance with high parameter efficiency.},
   }