Kuang-Huei Lee

I am a Senior Staff Research Scientist at Google DeepMind, where I work on science and applications of cognitive AI agents and reinforcement learning. Prior to joining the then Google Brain, I worked at Microsoft. I received my graduate degree in Computer Science from Carnegie Mellon University, and undergraduate degree in Mechanical Engineering from National Taiwan University.

Workshops Organized

Workshop on Robotics World Modeling, CoRL 2025
Workshop on Programmatic Reinforcement Learning, RLC 2025
Workshop on Building Physically Plausible World Models, ICML 2025
Workshop on Programmatic Representations for Agent Learning, ICML 2025

Selected Publications (All Publications)

Evolving Deeper LLM Thinking.
Kuang-Huei Lee*†, Ian Fischer*, Yueh-Hua Wu, Dave Marwood, Shumeet Baluja, Dale Schuurmans, Xinyun Chen (*: first author, †: senior author)
arXiv.
[paper]

Training-free Diffusion Model Alignment with Sampling Demons.
Po-Hung Yeh, Kuang-Huei Lee, Jun-Cheng Chen.
ICLR 2025.
[paper] [website and demo] [code]

The Design of the Barkour Benchmark for Robot Agility.
44 authors including Kuang-Huei Lee (last author).
IROS 2024.
[paper]

A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts.
Kuang-Huei Lee, Xinyun Chen, Hiroki Furuta, John Canny, Ian Fischer.
ICML 2024.
[paper] [website and demo]

Multimodal Web Navigation with Instruction-Finetuned Foundation Models.
Hiroki Furuta, Kuang-Huei Lee, Ofir Nachum, Yutaka Matsuo, Aleksandra Faust, Shixiang Shane Gu, Izzeddin Gur.
ICLR 2024.
[paper] [website]

Language to Rewards for Robotic Skill Synthesis.
Wenhao Yu*, Nimrod Gileadi*, Chuyuan Fu†, Sean Kirmani†, Kuang-Huei Lee†, Montse Gonzalez Arenas, Hao-Tien Lewis Chiang, Tom Erez, Leonard Hasenclever, Jan Humplik, Brian Ichter, Ted Xiao, Peng Xu, Andy Zeng, Tingnan Zhang, Nicolas Heess, Dorsa Sadigh, Jie Tan, Yuval Tassa, Fei Xia.
(*: Co-first authors, equal contribution, †: Core contributors)
CoRL 2023 Oral presentation.
[paper] [website] [Google AI Blog]

Barkour: Benchmarking Animal-level Agility with Quadruped Robots.
Ken Caluwaerts*, Atil Iscen*, J. Chase Kew*, Wenhao Yu*, Tingnan Zhang*, Daniel Freeman†, Kuang-Huei Lee†, Lisa Lee†, Stefano Saliceti†, Vincent Zhuang†, ..., (31 others), ..., Vincent Vanhoucke, and Jie Tan.
(*: Co-first authors, equal contribution, †: Core contributors)
Tech Report.
[paper] [website] [Google AI Blog] [YouTube]

RT-1: Robotics Transformer for Real-World Control at Scale.
51 authors in alphabetical order including Kuang-Huei Lee.
RSS 2023 Oral presentation.
[paper] [website] [Google AI Blog] [YouTube]

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.
43 authors in alphabetical order including Kuang-Huei Lee.
CoRL 2022 Special Innovation Award.
[paper] [website] [Google AI Blog] [YouTube]

Multi-Game Decision Transformers.
Kuang-Huei Lee*, Ofir Nachum*, Mengjiao Yang, Lisa Lee, Daniel Freeman, Winnie Xu, Sergio Guadarrama, Ian Fischer, Eric Jang, Henryk Michalewski, Igor Mordatch*
(*: Equal contribution)
NeurIPS 2022 Oral presentation.
[paper] [website] [code and pre-trained model] [Google AI Blog]

PI-ARS: Accelerating Evolution-Learned Visual-Locomotion with Predictive Information Representations.
Kuang-Huei Lee*, Ofir Nachum*, Tingnan Zhang, Sergio Guadarrama, Jie Tan, Wenhao Yu
(*: Equal contribution)
IROS 2022 Best Paper Finalist.
[paper] [supplementary video] [Google AI Blog]

Compressive Visual Representations.
Kuang-Huei Lee†, Anurag Arnab†, Sergio Guadarrama, John Canny, Ian Fischer†.
(†: Main contributors)
NeurIPS 2021.
[paper] [code and pre-trained models]

Predictive Information Accelerates Learning in RL.
Kuang-Huei Lee, Ian Fischer, Anthony Liu, Yijie Guo, Honglak Lee, John Canny, Sergio Guadarrama.
NeurIPS 2020.
[paper] [code]

Stacked Cross Attention for Image-Text Matching.
Kuang-Huei Lee, Xi Chen, Gang Hua, Houdong Hu, Xiaodong He.
ECCV 2018.
[paper] [website] [code]

CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise.
Kuang-Huei Lee, Xiaodong He, Lei Zhang, Linjun Yang.
CVPR 2018.
[paper] [website] [code] [dataset] [MSR Blog] [Bing Blog]

Software

TF-Agents. [GitHub]
I am a main contributor of the TF-Agents RL library.

Datasets

Food-101N: a dataset for learning to address label noise. [dataset]

Last Update: April 2026
Copyright 2026 Kuang-Huei Lee