Generalization to New Actions in Reinforcement Learning. - Ayush Jain 003; Andrew Szot; Joseph J. Lim (ICML, 2020)

Generalizable Imitation Learning from Observation via Inferring Goal Proximity. - Youngwoon Lee; Andrew Szot; Shao-Hua Sun; Joseph J. Lim (NeurIPS, 2021)

Habitat 2.0: Training Home Assistants to Rearrange their Habitat. - Andrew Szot; Alexander Clegg; Eric Undersander; Erik Wijmans; Yili Zhao; John M. Turner; Noah Maestre; Mustafa Mukadam; Devendra Singh Chaplot; Oleksandr Maksymets; Aaron Gokaslan; Vladimir Vondrus; et al. (NeurIPS, 2021)

Housekeep: Tidying Virtual Households Using Commonsense Reasoning. - Yash Kant; Arun Ramachandran; Sriram Yenamandra; Igor Gilitschenski; Dhruv Batra; Andrew Szot; Harsh Agrawal (ECCV (39), 2022)

Retrospectives on the Embodied AI Workshop. - Matt Deitke; Dhruv Batra; Yonatan Bisk; Tommaso Campari; Angel X. Chang; Devendra Singh Chaplot; Changan Chen; Claudia Pérez-D'Arpino; Kiana Ehsani; Ali Farhadi; Li Fei-Fei 001; Anthony G. Francis; et al. (CoRR, 2022)

Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at 100k Steps-Per-Second. - Vincent-Pierre Berges; Andrew Szot; Devendra Singh Chaplot; Aaron Gokaslan; Roozbeh Mottaghi; Dhruv Batra; Eric Undersander (CVPR, 2023)

Skill Transformer: A Monolithic Policy for Mobile Manipulation. - Xiaoyu Huang; Dhruv Batra; Akshara Rai; Andrew Szot (ICCV, 2023)

BC-IRL: Learning Generalizable Reward Functions from Demonstrations. - Andrew Szot; Amy Zhang 001; Dhruv Batra; Zsolt Kira; Franziska Meier (ICLR, 2023)

Adaptive Coordination in Social Embodied Rearrangement. - Andrew Szot; Unnat Jain; Dhruv Batra; Zsolt Kira; Ruta Desai; Akshara Rai (ICML, 2023)

Large Language Models as Generalizable Policies for Embodied Tasks. - Andrew Szot; Max Schwarzer; Harsh Agrawal; Bogdan Mazoure; Walter Talbott; Katherine Metcalf; Natalie Mackraz; R. Devon Hjelm; Alexander Toshev (CoRR, 2023)

An Extensible, Data-Oriented Architecture for High-Performance, Many-World Simulation. - Brennan Shacklett; Luc Guy Rosenzweig; Zhiqiang Xie; Bidipta Sarkar; Andrew Szot; Erik Wijmans; Vladlen Koltun; Dhruv Batra; Kayvon Fatahalian (ACM Trans. Graph., 2023)

Reinforcement Learning via Auxiliary Task Distillation. - Abhinav Narayan Harish; Larry Heck; Josiah P. Hanna; Zsolt Kira; Andrew Szot (ECCV (81), 2024)

Habitat 3.0: A Co-Habitat for Humans, Avatars, and Robots. - Xavier Puig; Eric Undersander; Andrew Szot; Mikael Dallaire Cote; Tsung-Yen Yang; Ruslan Partsey; Ruta Desai; Alexander Clegg; Michal Hlavac; So Yeon Min; Vladimir Vondrus; Théophile Gervet; et al. (ICLR, 2024)

Large Language Models as Generalizable Policies for Embodied Tasks. - Andrew Szot; Max Schwarzer; Harsh Agrawal; Bogdan Mazoure; Rin Metcalf; Walter Talbott; Natalie Mackraz; R. Devon Hjelm; Alexander T. Toshev (ICLR, 2024)

Grounding Multimodal Large Language Models in Actions. - Andrew Szot; Bogdan Mazoure; Harsh Agrawal; R. Devon Hjelm; Zsolt Kira; Alexander Toshev (NeurIPS, 2024)

Towards Open-World Mobile Manipulation in Homes: Lessons from the Neurips 2023 HomeRobot Open Vocabulary Mobile Manipulation Challenge. - Sriram Yenamandra; Arun Ramachandran; Mukul Khanna; Karmesh Yadav; Jay Vakil; Andrew Melnik; Michael Büttner; Leon Harz; Lyon Brown; Gora Chand Nandi; Arjun P. S; Gaurav Kumar Yadav; et al. (CoRR, 2024)

ReLIC: A Recipe for 64k Steps of In-Context Reinforcement Learning for Embodied AI. - Ahmad Elawady; Gunjan Chhablani; Ram Ramrakhya; Karmesh Yadav; Dhruv Batra; Zsolt Kira; Andrew Szot (CoRR, 2024)

From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons. - Andrew Szot; Bogdan Mazoure; Omar Attia; Aleksei Timofeev; Harsh Agrawal; R. Devon Hjelm; Zhe Gan; Zsolt Kira; Alexander Toshev (CVPR, 2025)