| CARVIEW |
I am a final year Ph.D. candidate at the University of Southern California coadvised by Erdem Bıyık (LiRA Lab) and Stephen Tu. I am interested in efficient robot learning from various forms of natural human feedback, such as gaze, hand demonstrations, videos, and preferences. I am also interested in reinforcement learning for efficient adaptation of agents to new tasks and environments. I had the pleasure to intern at Google Gemini to work on post-training RL for reasoning models and with Google Research working on meta-RL on dynamic long-horizon MDPs. I also interned at Meta Reality Lab building task-oriented dialogue systems using LLMs.
Prior to joining USC, I spent a summer (during the pandemic) as a visiting scholar at CMU working with Changliu Liu. I graduated from the University of Michigan with a Masters in Robotics and Bachelors in Computer Science where I worked with Wilka Carvalho and Honglak Lee. I had the pleasure to intern at Amazon, Invisible.ai, Google Ads, Luminar and Socratic.
Feel free to say hi: anthony dot liang at usc dot edu
News
| May 2025 | Starting Research Intern with the Google Gemini team in New York! |
| Sept 2024 | DynaMITE-RL accepted to NeurIPS 2024 as a poster. |
| June 2024 | PromptDTLA accepted to ICML 2024 ICL Workshop and DynaMITE-RL accepted to AutoRL Workshop |
| June 2024 | ViSaRL accepted to International Conference on Intelligent Robots and Systems (IROS 2024) |
| May 2023 | Student Researcher at Google with the Machine Intelligence group |
| May 2022 | Started at Meta Reality Lab as an NLP Research Intern working on Task-Oriented Dialogue Systems using LLMs |
| Sept 2021 | Started my Ph.D. at USC with the GLAMOR group! |
| May 2021 | Applied Scientist Intern at Amazon |
| Oct 2020 | Preprint out on arXiv: Reinforcement Learning for Sparse-Reward Object-Interaction Tasks |
Publications
Preprints
🍌 Plantain: Plan-Answer Interleaved Reasoning
Anthony Liang, Jonathan Berant, Adam Fisch, Abhimanyu Goyal, Kalpesh Krishna†, Jacob Eisenstein†
Work done during Google internship
SPUR: Scaling Reward Learning from Human Demonstrations
Anthony Liang*, Yigit Korkmaz*, Jiahui Zhang*, Jesse Zhang*, Abrar Anwar, Sidhant Kaushik, Yufei Wang, Yu Xiang, David Held, Dieter Fox, Abhishek Gupta, Stephen Tu, Erdem Bıyık
CoRL 2025 Workshop Eval Deploy / NeurIPS 2025 Workshop on Embodied World Models
Conference Papers
HAND Me the Data: Fast Robot Adaptation via Hand Path Retrieval
RHODES: Reducing Human Oversight via Disagreement and Exploration for Safe Reinforcement Learning
Jaiv Doshi*, Anthony Liang*, Yigit Korkmaz, Erdem Bıyık
In Submission to ICML 2025
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments
Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh
International Joint Conference on Artificial Intelligence 2021
Workshop Papers
In-Context Generalization to New Tasks From Unlabeled Observation Data
Anthony Liang, Pavel Czempin, Yutai Zhou, Stephen Tu, Erdem Bıyık
1st ICL Workshop at ICML 2024
Transformer Adapters for Robot Learning
Anthony Liang, Ishika Singh, Karl Pertsch, Jesse Thomason
CoRL 2022 Workshop on Pretraining for Robot Learning
Spotlight Talk
Teaching
| CSCI 699: Robot Learning | Fall 2024 |
| CSCI 499: Interactive Natural Language Processing | Fall 2023 |
| EECS 442: Computer Vision | Winter 2021 |
| EECS 498: Algorithmic Robotics | Winter 2020 |
| EECS 504: Graduate Computer Vision | Fall 2020 |
| EECS 280: Introduction to Programming and Data Structures | Fall 2018, Winter 2018, Fall 2019 |