About me

Position:
Assistant Professor

Affiliation:
Shanghai Innovation Institute

Email:
jjgongjj+wk[AT]gmail.com

I am an Assistant Professor at the Shanghai Innovation Institute, where my research explores the cutting edge of Embodied AI. My primary goal is to push the frontiers of multimodal large models into the physical world, bridging the gap between digital intelligence and physical interaction. My research interests span Machine Learning (ML), Reinforcement Learning (RL) and Natural Language Processing (NLP), with a particular focus on Large Language Models (LLMs). Additionally, I have a deep passion for advanced Generative Models, including Diffusion Models, Flow Matching, and Bayesian Flow Networks.

Before joining the Institute, I was a Postdoctoral Fellow at the Institute for AI Industrial Research, Tsinghua University, working with Prof. Weiying Ma and Prof. Hao Zhou, focusing on bio-molecular generative models. I obtained my Ph.D. from Fudan University, advised by Prof. Xipeng Qiu and Prof. Xuanjing Huang, where my work concentrated on Natural Language Processing (NLP). I have served as reviewer for top-tier conferences including NeurIPS, ICML, ICLR, ACL, EMNLP and AAAI, and was honored to serve as Area Chair for ICLR and NeurIPS.

Feel free to reach out to me if you are interested in building cool things together!

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News

• [May 2026] “Learning to Move Before Learning to Do: Task-Agnostic Pretraining for VLAs” was accepted at ICML 2026.
• [May 2026] “HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control” was accepted at ICML 2026.
• [Feb 2026] “SRPO: Self-Referential Policy Optimization for Vision-Language-Action Models” was accepted at CVPR 2026.
• [Feb 2026] “Libero-Plus: In-Depth Robustness Analysis of Vision-Language-Action Models” was accepted at CVPR 2026.
• [Jan 2026] “FASTer: Toward Efficient Autoregressive Vision Language Action Modeling via Neural Action Tokenization” was accepted at ICLR 2026.
• [May 2025] “Steering Protein Family Design Through Profile Bayesian Flow” was accepted at ICLR 2025 as an Oral Presentation.

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Selected Publications

2026

1. HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control
   Li Ji, Siyin Wang, Pengfang Qian, Xiaopeng Yu, Yihai Tian, Zhaoye Fei, Jingjing Gong, Xipeng Qiu
   ICML 2026

2. Learning to Move Before Learning to Do: Task-Agnostic Pretraining for VLAs
   Junhao Shi, Siyin Wang, Xiaopeng Yu, Li Ji, Jingjing Gong, Xipeng Qiu
   ICML 2026

3. Libero-Plus: In-Depth Robustness Analysis of Vision-Language-Action Models
   Senyu Fei, Siyin Wang, Junhao Shi, Zihao Dai, Jikun Cai, Pengfang Qian, Li Ji, Xinzhe He, Shiduo Zhang, Zhaoye Fei, Jinlan Fu, Jingjing Gong, Xipeng Qiu
   CVPR 2026

4. SRPO: Self-Referential Policy Optimization for Vision-Language-Action Models
   Senyu Fei, Siyin Wang, Li Ji, Ao Li, Shiduo Zhang, Liming Liu, Jinlong Hou, Jingjing Gong, Xianzhong Zhao, Xipeng Qiu
   CVPR 2026

5. FASTer: Toward Efficient Autoregressive Vision Language Action Modeling via Neural Action Tokenization
   Yicheng Liu, Shiduo Zhang, Zibin Dong, Baijun Ye, Tianyuan Yuan, Xiaopeng Yu, Linqi Yin, Chenhao Lu, Junhao Shi, Luca Jiang-Tao Yu, Liangtao Zheng, Tao Jiang, Jingjing Gong, Xipeng Qiu, Hang Zhao
   ICLR 2026

6. RoboOmni: Proactive Robot Manipulation in Omni-Modal Context
   Siyin Wang, Jinlan Fu, Feihong Liu, Xinzhe He, Huangxuan Wu, Junhao Shi, Kexin Huang, Zhaoye Fei, Jingjing Gong, Zuxuan Wu, Yu-Gang Jiang, See-Kiong Ng, Tat-Seng Chua, Xipeng Qiu
   ICLR 2026

2025

1. Steering Protein Family Design Through Profile Bayesian Flow
   Jingjing Gong, Yu Pei, Siyu Long, Yuxuan Song, Zhe Zhang, Wenhao Huang, Ziyao Cao, Shuyi Zhang, Hao Zhou, Wei-Ying Ma
   ICLR 2025, (Oral Presentation)

2. A Periodic Bayesian Flow for Material Generation
   Hanlin Wu, Yuxuan Song, Jingjing Gong, Ziyao Cao, Yawen Ouyang, Jianbing Zhang, Hao Zhou, Wei-Ying Ma, Jingjing Liu
   ICLR 2025

3. Smooth Interpolation for Improved Discrete Graph Generative Models
   Yuxuan Song, Juntong Shi, Jingjing Gong, Minkai Xu, Stefano Ermon, Hao Zhou, Wei-Ying Ma
   ICML 2025

4. Accelerating 3D Molecule Generative Models with Trajectory Diagnosis
   Zhilong Zhang, Yuxuan Song, Yichun Wang, Jingjing Gong, Hanlin Wu, Dongzhan Zhou, Hao Zhou, Wei-Ying Ma
   NeurIPS 2025

5. World-Aware Planning Narratives Enhance Large Vision-Language Model Planner
   Junhao Shi, Zhaoye Fei, Siyin Wang, Qipeng Guo, Jingjing Gong, Xipeng Qiu
   NeurIPS 2025

6. ShortListing Model: A Streamlined Simplex Diffusion for Discrete Variable Generation
   Yuxuan Song, Zhe Zhang, Yu Pei, Jingjing Gong, Qiying Yu, Zheng Zhang, Mingxuan Wang, Hao Zhou, Jingjing Liu, Wei-Ying Ma
   NeurIPS 2025, (Poster)

2024

1. MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space
   Yanru Qu, Keyue Qiu, Yuxuan Song, Jingjing Gong, Jiawei Han, Mingyue Zheng, Hao Zhou, Wei-Ying Ma
   ICML 2024

2. Unified Generative Modeling of 3D Molecules via Bayesian Flow Networks
   Yuxuan Song, Jingjing Gong, Hao Zhou, Mingyue Zheng, Jingjing Liu, Wei-Ying Ma
   ICLR 2024, (Oral Presentation)

2023

1. Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation
   Yuxuan Song, Jingjing Gong, Minkai Xu, Ziyao Cao, Yanyan Lan, Stefano Ermon, Hao Zhou, Wei-Ying Ma
   NeurIPS 2023

2. Coarse-to-Fine: A Hierarchical Diffusion Model for Molecule Generation in 3D
   Bo Qiang, Yuxuan Song, Minkai Xu, Jingjing Gong, Bowen Gao, Hao Zhou, Wei-Ying Ma, Yanyan Lan
   ICML 2023