Recent Talks

• [2025/3] Invited talk at AAAI 2025: How Vision and Language Models Are Changing Decision-Making
• [2025/2] Course lecture at Stanford CS223A: Perception in Robotics
• [2024/11] Course lecture at Stanford EECS227: Pretrained Foundation Models for Robotics
• [2024/7] Seminar Talk at Stanford
• [2023/12] Invited Talk at NeurIPS 2023 Workshop on Diffusion Models
• [2023/8] Invited Talk at Google
• [2023/8] Diffusion Models Course at SIGGRAPH
• [2023/5] Invited Talk at UC Berkeley
• [2023/4] Invited Talk at Nanyang Technological University
• [2023/2] Invited Talk at Columbia
• [2023/2] Invited Talk at UIUC
• [2023/2] Invited Talk at UT Austin
• [2022/12] Invited Talk at UC San Diego
• [2022/11] Invited Talk at Cornell Tech
• [2022/11] Invited Talk at UC Berkeley
• [2022/11] Invited Talk at Stanford
• [2022/11] Invited Talk at Northeastern

Workshops / Tutorials Organizer

• Knowledge in Generative Models at ECCV 2024
• Diffusion Models Course at SIGGRAPH 2023
• Social Intelligence in Humans and Robots at ICRA 2021, RSS 2022, RSS 2023
• MIT Visual Computing Workshop 2021
  
• Wider Face and Person Challenge at ICCV 2019

News

• I have been awarded CIFAR AI Chair Award 2024.
• I have been selected as one of the EECS Rising Stars 2022.
• I have been selected as an Outstanding Reviewer for ICML 2022.
• I have been selected as a finalist for 2022 Qualcomm Fellowship. Thanks, Qualcomm!
• I have been awarded 2021 Facebook Research Fellowship. Thanks, Facebook!
• I have been awarded 2019 Adobe Research Fellowship. Thanks, Adobe!
• A summary of our recent works on Compositional Generalization.
• A summary of our recent works on Energy-based Models.

Datasets and Environments

• VirtualHome multi-agent embodied environment for household activities
• V-HICO dataset for video-based human-object interaction detection
• CUHK-SYSU dataset for person re-identification
• CUHK-PEDES dataset for natural language based person re-identification

Selected Publications [Full List] ( show by date / show by topic)
Research Topics: Robotics Learning / Generative Modeling / Compositional Foundation Models

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(* indicates equal contribution, † indicates equal advising)

Unified Video Action Model
Shuang Li, Yihuai Gao, Dorsa Sadigh, and Shuran Song
arXiv 2025
[Project] [Paper] [Code]

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Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains
Vighnesh Subramaniam*, Yilun Du*, Joshua B. Tenenbaum, Antonio Torralba, Shuang Li†, Igor Mordatch†
ICLR 2025
[Project] [Paper] [Code]

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Compositional Foundation Models for Hierarchical Planning
Anurag Ajay*, Seungwook Han*, Yilun Du*, Shuang Li, Abhi Gupta, Tommi Jaakkola,
Joshua B. Tenenbaum, Leslie Kaelbling, Akash Srivastava, and Pulkit Agrawal
NeurIPS 2023
[Project] [Paper] [Code]
Press coverage: MIT News, MIT CSAIL News

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ConceptFusion: Open-set Multimodal 3D Mapping
Krishna Murthy Jatavallabhula, Alihusein Kuwajerwala, Qiao Gu, Mohd Omama, Tao Chen,
Shuang Li, Ganesh Iyer, Soroush Saryazdi, Nikhil Keetha, Ayush Tewari, Joshua B. Tenenbaum,
Celso Miguel de Melo, Madhava Krishna, Liam Paull, Florian Shkurti, and Antonio Torralba
RSS 2023
CVPR 2023 Demos (and Art Gallery)
ICRA Pretraining for Robotics Workshop 2023
[Project] [Paper] [Video]

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Composing Ensembles of Pre-trained Models via Iterative Consensus
Shuang Li, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba, and Igor Mordatch
ICLR 2023
[Project] [Paper] [Github]

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Pre-Trained Language Models for Interactive Decision-Making
Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar⁺, Jacob Andreas, Igor Mordatch⁺, Antonio Torralba⁺, and Yuke Zhu⁺
Junior authors are ordered based on their contributions and senior authors⁺ are ordered alphabetically
NeurIPS 2022, Oral
[Project] [Paper] [Code]

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Compositional Visual Generation with Composable Diffusion Models
Nan Liu*, Shuang Li*, Yilun Du*, Antonio Torralba, and Joshua B. Tenenbaum (*equal contribution)
ECCV 2022
[Project] [Paper] [Github] [Colab] [Demo]
Press coverage: MIT News, MIT CSAIL News

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Energy-Based Models for Continual Learning
Shuang Li, Yilun Du, Gido M. van de Ven, and Igor Mordatch
CoLLAs 2022, Oral
ICLR EBM Workshop 2021, Oral
[Project] [Paper] [Code]

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3D Neural Scene Representations for Visuomotor Control
Yunzhu Li*, Shuang Li*, Vincent Sitzmann, Pulkit Agrawal, and Antonio Torralba (*equal contribution)
CoRL 2021, Oral
RSS Visual Learning and Reasoning for Robotics Workshop 2021
[Project] [Paper] [Code]

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Learning to Compose Visual Relations
Nan Liu*, Shuang Li*, Yilun Du*, Joshua B. Tenenbaum, and Antonio Torralba (*equal contribution)
NeurIPS 2021, Spotlight
NeurIPS Controllable Generative Modeling Workshop 2021, Outstanding Paper Award
[Project] [Paper] [Code]
Press coverage: MIT News, MIT CSAIL News

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Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration
Xavier Puig, Tianmin Shu, Shuang Li, Zilin Wang, Joshua B. Tenenbaum, Sanja Fidler, and Antonio Torralba
ICLR 2021, Spotlight
NeurIPS Cooperative AI Workshop 2020, Best Paper Award
[Project] [Paper] [Code] [Video] [VirtualHome]

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Compositional Visual Generation with Energy Based Models
Yilun Du, Shuang Li, and Igor Mordatch
NeurIPS 2020, Spotlight
[Project] [Paper] [Code]

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Person Search with Natural Language Description
Shuang Li, Tong Xiao, Hongsheng Li, Bolei Zhou, Dayu Yue, and Xiaogang Wang
CVPR 2017
[Paper] [Code]

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Joint Detection and Identification Feature Learning for Person Search
Tong Xiao*, Shuang Li*, Bochao Wang, Liang Lin, and Xiaogang Wang (*equal contribution)
CVPR 2017, Spotlight
[Paper] [Code]

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Selected Honors

• CIFAR AI Chair, 2024 [Link]
• EECS Rising Stars, 2022 [Link]
• ICML Outstanding Reviewer, 2022 [Link]
• Qualcomm Fellowship Finalist, 2022 [Link]
• Facebook Research Fellowship, 2021 [Link]
• Adobe Research Fellowship, 2019 [Link]
• MIT Seneff-Zue CS Fellowship, 2018
• Outstanding Students Award, CUHK, 2018

Contact