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I am an Assistant Professor of Interactive Computing at Georgia Tech and the Autonomy Research Lead at Walden Robotics.
Research Opportunities: If you are a current Georgia Tech student looking for research experience in the lab, please fill out this form. The form is the best way to reach me about research opportunities in my lab, and is much more reliable than email. |
News
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[Aug 2026]: I've officially started at Georgia Tech as an Assistant Professor of Interactive Computing – the lab is up and running in Atlanta!
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[May 2025]: I am thrilled to be joining Georgia Tech as an Assistant Professor of Interactive Computing starting in Fall 2026! I'm honored to be joining an amazing group of faculty and students, and building a new lab to work at the intersection of robotics, machine learning, and human-robot interaction.
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[Nov 2024]: Looking forward to being at CoRL 2024 presenting both Vocal Sandbox and OpenVLA; don't miss Jenn's talk on Vocal Sandbox during Oral Session 3! I'll also be at the afternoon panel at the LangRob workshop on Saturday – hope to see y'all in Munich!
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[Oct 2024]: Excited to share "Vocal Sandbox: Continual Learning and Adaptation for Situated Human-Robot Collaboration" – we introduce a new framework for building robots that can progressively improve over time, learning new skills, visual concepts, and planning behaviors from their partners in real time. Check out our project page for videos, especially our two hour long demo deploying a Vocal Sandbox system for LEGO stop-motion animation!
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[Jun 2024]: Introducing "OpenVLA: an Open-Source Vision-Language-Action Model" – a generalist policy for robotic manipulation, built directly using the VLMs/codebase we developed in Prismatic. Trained on almost 1M demonstrations from Open X-Embodiment (and DROID), not only do we get some great zero-shot performance, but you can efficiently fine-tune for new robots and tasks! Huge shout out to my co-leads Moo Jin Kim and Karl Pertsch; check out our models on HuggingFace, and our codebase.
Publications
2026
ReSteer: Quantifying and Refining the Steerability of Multitask Robot Policies
Zhenyang Chen, Alan Tian*, Liquan Wang*, Benjamin Joffe, Yingyan Celine Lin, Yuxiao Chen, Siddharth Karamcheti†, Danfei Xu†.
Robotics: Science and Systems (RSS), 2026.
[pdf] [homepage] [video]
A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation
Toyota Research Institute - Large Behavior Models Team.
Science Robotics, 2026.
[pdf] [homepage] [overview video]
2025
ProVox: Personalization and Proactive Planning for Situated Human-Robot Collaboration
Jennifer Grannen, Siddharth Karamcheti, Blake Wulfe, Dorsa Sadigh.
IEEE Robotics and Automation Letters (RA-L), 2025.
Presentation at ICRA 2026.
[pdf] [homepage]
2024
Vocal Sandbox: Continual Learning and Adaptation for Situated Human-Robot Collaboration
Jennifer Grannen*, Siddharth Karamcheti*, Suvir Mirchandani, Percy Liang, Dorsa Sadigh.
Conference on Robot Learning (CoRL), November 2024.
Oral Presentation
[pdf] [homepage]
OpenVLA: An Open-Source Vision-Language-Action Model
Moo Jin Kim*, Karl Pertsch*, Siddharth Karamcheti*, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Foster, Grace Lam,
Pannag Sanketi, Quan Vuong, Thomas Kollar, Ben Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, Chelsea Finn.
Conference on Robot Learning (CoRL), November 2024.
Outstanding Paper Award Finalist
[pdf] [homepage] [models] [code]
DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset
DROID Collaboration (Research Lead – Data Curation & Annotation, Lab Lead).
Robotics: Science and Systems (RSS), July 2024.
[pdf] [homepage] [dataset visualizer] [colab]
Prismatic VLMs: Investigating the Design Space of Vision-Language Models
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, Dorsa Sadigh.
International Conference on Machine Learning (ICML), July 2024.
[pdf] [code & models] [code - evaluation]
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Open X-Embodiment Collaboration.
IEEE International Conference on Robotics and Automation (ICRA), May 2024.
Best Paper Award
[pdf] [homepage] [datasets] [code]
2023
Language-Driven Representation Learning for Robotics
Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang.
Robotics: Science and Systems (RSS), July 2023.
Best Paper Award Finalist
[pdf] [homepage] [code - models] [code - evaluation]
“No, to the Right” – Online Language Corrections for Robotic Manipulation via Shared Autonomy
Yuchen Cui*, Siddharth Karamcheti*, Raj Palleti, Nidhya Shivakumar, Percy Liang, Dorsa Sadigh.
ACM/IEEE International Conference on Human Robot Interaction (HRI), March 2023.
[pdf] [homepage] [code]
2022
Eliciting Compatible Demonstrations for Multi-Human Imitation Learning
Kanishk Gandhi, Siddharth Karamcheti, Madeline Liao, Dorsa Sadigh.
Conference on Robot Learning (CoRL), December 2022.
[pdf] [homepage]
What Makes Representation Learning from Videos Hard for Control?
Tony Z. Zhao, Siddharth Karamcheti, Thomas Kollar, Chelsea Finn, Percy Liang.
2nd Workshop on Scaling Robot Learning @ RSS 2022, June 2022.
(Workshop) Best Paper Award Finalist
[pdf]
Shared Autonomy for Robotic Manipulation with Language Corrections
Siddharth Karamcheti*, Raj Palleti*, Yuchen Cui, Percy Liang, Dorsa Sadigh.
Workshop on Learning with Natural Language Supervision (NL-Supervision) @ ACL 2022, May 2022.
[pdf]
2021
ELLA: Exploration through Learned Language Abstraction
Suvir Mirchandani, Siddharth Karamcheti, Dorsa Sadigh.
Conference on Neural Information Processing Systems (NeurIPS), December 2021.
[pdf] [talk] [slides]
[code]
LILA: Language-Informed Latent Actions
Siddharth Karamcheti*, Megha Srivastava*, Percy Liang, Dorsa Sadigh.
Conference on Robot Learning (CoRL), November 2021.
[pdf] [homepage] [code] [poster]
On the Opportunities and Risks of Foundation Models
Center for Research on Foundation Models (CRFM) – 100+ authors, directed by Percy Liang.
       - Robotics (§2.3):
Siddharth Karamcheti (Lead), Annie Chen, Suvir Mirchandani, Suraj Nair, Krishnan Srinivasan, Kyle Hsu,
Jeannette Bohg, Dorsa Sadigh, Chelsea Finn.
       - Interaction (§2.5): Joon Sung Park,
Chris Donahue, Mina Lee, Siddharth Karamcheti, Dorsa Sadigh, Michael Bernstein.
[pdf] [homepage]
[workshop] [press]
Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering
Siddharth Karamcheti, Ranjay Krishna, Li Fei-Fei, Christopher D. Manning.
Annual Meeting of the Association for Computational Linguistics (ACL-IJCNLP), August 2021.
Outstanding Paper Award
[pdf] [talk]
[slides] [code] [other coverage]
Targeted Data Acquisition for Evolving Negotiation Agents
Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuéllar, Dorsa Sadigh.
International Conference on Machine Learning (ICML), July 2021.
[pdf] [talk] [slides]
Learning Visually Guided Latent Actions for Assistive Teleoperation
Siddharth Karamcheti, Albert J. Zhai, Dylan P. Losey, Dorsa Sadigh.
Learning for Dynamics and Control (L4DC), June 2021.
[pdf] [talk] [slides] [code] [poster]
2020
Learning Adaptive Language Interfaces through Decomposition
Siddharth Karamcheti, Dorsa Sadigh, Percy Liang.
Workshop for Interactive and Executable Semantic Parsing (IntEx-SemPar) @ EMNLP 2020, November 2020.
[pdf] [slides]
Generating Interactive Worlds with Text
Angela Fan*, Jack Urbanek*, Pratik Ringshia, Emily Dinan, Emma Qian, Siddharth Karamcheti, Shrimai Prabhumoye, Douwe Kiela, Tim Rocktäschel, Arthur Szlam, and Jason Weston.
Association for the Advancement of Artificial Intelligence (AAAI), February 2020
[pdf] [dataset]
2019
Finding Generalizable Evidence by Learning to Convince Q&A Models
Ethan Perez, Siddharth Karamcheti, Rob Fergus, Jason Weston, Douwe Kiela, and Kyunghyun Cho.
Empirical Methods in Natural Language Processing (EMNLP), November 2019
[pdf] [blog post] [code]
Learning to Speak and Act in a Fantasy Text Adventure Game
Jack Urbanek, Angela Fan, Siddharth Karamcheti, Saachi Jain, Samuel Humeau, Emily Dinan, Tim Rocktäschel, Douwe Kiela, Arthur Szlam, and Jason Weston.
Empirical Methods in Natural Language Processing (EMNLP), November 2019
[pdf] [dataset]
Improving Grey-Box Fuzzing by Modeling Program Control Flow
Siddharth Karamcheti, Gideon Mann, and David Rosenberg
Workshop on Machine Learning for Software Engineering (ML4SE), June 2019
[pdf] [slides]
Grounding Natural Language Instructions to Semantic Goal Representations for Abstraction and Generalization
Dilip Arumugam*, Siddharth Karamcheti*, Nakul Gopalan, Edward C. Williams, Mina Rhee, Lawson L.S. Wong, and Stefanie Tellex
Autonomous Robots (AuRO), February 2019
[free-to-read pdf]
2018
Adaptive Grey-Box Fuzz Testing with Thompson Sampling
Siddharth Karamcheti, Gideon Mann, and David Rosenberg
11th ACM Workshop on Artificial Intelligence and Security (AISEC), October 2018
Oral Presentation
[pdf] [slides]
2017
Modeling Latent Attention within Neural Networks
Christopher Grimm, Dilip Arumugam, Siddharth Karamcheti, David Abel, Lawson L.S. Wong, and Michael Littman
Preprint
[pdf]
A Tale of Two DRAGGNs: A Hybrid Approach for Interpreting Action-Oriented and Goal-Oriented Instructions
Siddharth Karamcheti, Edward C. Williams, Dilip Arumugam, Mina Rhee, Nakul Gopalan, Lawson L.S. Wong, and Stefanie Tellex
1st Workshop in Language Grounding for Robotics (RoboNLP) @ ACL, August 2017
Best Paper Award
[pdf]
Accurately and Efficiently Interpreting Human-Robot Instructions of Varying Granularities
Dilip Arumugam*, Siddharth Karamcheti*, Nakul Gopalan, Lawson L.S. Wong, and Stefanie Tellex
Robotics: Science and Systems (RSS), June 2017
[pdf]
Blog Posts
The Annotated S4 – Efficiently Modeling Long Sequences with Structured State Spaces
Sasha Rush and Siddharth Karamcheti – January, 2022.
[ICLR blog track] [code] [original paper]
Mistral – A Journey towards Reproducible Language Model Training
Siddharth Karamcheti* and Laurel Orr* – August, 2021.
Team: Jason Bolton, Tianyi Zhang, Karan Goel, Avanika Narayan, Rishi Bommasani, Deepak Narayanan
Advisors: Tatsunori Hashimoto, Dan Jurafsky, Christopher D. Manning, Christopher Potts, Christopher RĂ©, Percy Liang
[code] [checkpoints] [talk]