Not All Neural Embeddings are Born Equal. - Felix Hill; KyungHyun Cho; Sébastien Jean; Coline Devin; Yoshua Bengio (CoRR, 2014)

Embedding Word Similarity with Neural Machine Translation. - Felix Hill; Kyunghyun Cho; Sébastien Jean; Coline Devin; Yoshua Bengio (ICLR (Workshop), 2015)

Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments. - Eric Tzeng; Coline Devin; Judy Hoffman; Chelsea Finn; Xingchao Peng; Sergey Levine; Kate Saenko; Trevor Darrell (CoRR, 2015)

Adapting Deep Visuomotor Representations with Weak Pairwise Constraints. - Eric Tzeng; Coline Devin; Judy Hoffman; Chelsea Finn; Pieter Abbeel; Sergey Levine; Kate Saenko; Trevor Darrell (WAFR, 2016)

Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning. - Abhishek Gupta 004; Coline Devin; Yuxuan Liu 001; Pieter Abbeel; Sergey Levine (ICLR (Poster), 2017)

Learning modular neural network policies for multi-task and multi-robot transfer. - Coline Devin; Abhishek Gupta 004; Trevor Darrell; Pieter Abbeel; Sergey Levine (ICRA, 2017)

Grasp2Vec: Learning Object Representations from Self-Supervised Grasping. - Eric Jang; Coline Devin; Vincent Vanhoucke; Sergey Levine (CoRL, 2018)

Deep Object-Centric Representations for Generalizable Robot Learning. - Coline Devin; Pieter Abbeel; Trevor Darrell; Sergey Levine (ICRA, 2018)

Deep Object-Centric Policies for Autonomous Driving. - Dequan Wang; Coline Devin; Qi-Zhi Cai; Fisher Yu 001; Trevor Darrell (ICRA, 2019)

Monocular Plan View Networks for Autonomous Driving. - Dequan Wang; Coline Devin; Qi-Zhi Cai; Philipp Krähenbühl; Trevor Darrell (IROS, 2019)

Compositional Plan Vectors. - Coline Devin; Daniel Geng; Pieter Abbeel; Trevor Darrell; Sergey Levine (NeurIPS, 2019)

Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control. - Coline Devin; Daniel Geng; Pieter Abbeel; Trevor Darrell; Sergey Levine (CoRR, 2019)

SMiRL: Surprise Minimizing RL in Dynamic Environments. - Glen Berseth; Daniel Geng; Coline Devin; Chelsea Finn; Dinesh Jayaraman; Sergey Levine (CoRR, 2019)

Learning To Reach Goals Without Reinforcement Learning. - Dibya Ghosh; Abhishek Gupta 004; Justin Fu; Ashwin Reddy; Coline Devin; Benjamin Eysenbach; Sergey Levine (CoRR, 2019)

Self-Supervised Goal-Conditioned Pick and Place. - Coline Devin; Payam Rowghanian; Chris Vigorito; William Richards; Khashayar Rohanimanesh (CoRR, 2020)

Modularity Improves Out-of-Domain Instruction Following. - Rodolfo Corona; Daniel Fried; Coline Devin; Dan Klein 001; Trevor Darrell (CoRR, 2020)

Compositionality and Modularity for Robot Learning. - Coline Devin (2020)

Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes. - Alex X. Lee; Coline Manon Devin; Yuxiang Zhou; Thomas Lampe; Konstantinos Bousmalis; Jost Tobias Springenberg; Arunkumar Byravan; Abbas Abdolmaleki; Nimrod Gileadi; David Khosid; Claudio Fantacci; José Enrique Chen; et al. (CoRL, 2021)

Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation. - Charles Sun; Jedrzej Orbik; Coline Manon Devin; Brian H. Yang; Abhishek Gupta 004; Glen Berseth; Sergey Levine (CoRL, 2021)

SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments. - Glen Berseth; Daniel Geng; Coline Manon Devin; Nicholas Rhinehart; Chelsea Finn; Dinesh Jayaraman; Sergey Levine (ICLR, 2021)

Learning to Reach Goals via Iterated Supervised Learning. - Dibya Ghosh; Abhishek Gupta 004; Ashwin Reddy; Justin Fu; Coline Manon Devin; Benjamin Eysenbach; Sergey Levine (ICLR, 2021)

Modular Networks for Compositional Instruction Following. - Rodolfo Corona; Daniel Fried; Coline Devin; Dan Klein 001; Trevor Darrell (NAACL-HLT, 2021)

ReLMM: Practical RL for Learning Mobile Manipulation Skills Using Only Onboard Sensors. - Charles Sun; Jedrzej Orbik; Coline Devin; Brian H. Yang; Abhishek Gupta 004; Glen Berseth; Sergey Levine (CoRR, 2021)

How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation. - Alex X. Lee; Coline Devin; Jost Tobias Springenberg; Yuxiang Zhou; Thomas Lampe; Abbas Abdolmaleki; Konstantinos Bousmalis (IROS, 2022)

RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Devin; Alex X. Lee; Maria Bauzá 001; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (CoRR, 2023)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models. - Open X.-Embodiment Collaboration; Abhishek Padalkar; Acorn Pooley; Ajinkya Jain; Alex Bewley; Alexander Herzog; Alex Irpan; Alexander Khazatsky; Anant Raj; Anikait Singh; Anthony Brohan; Antonin Raffin; et al. (CoRR, 2023)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. - Abby O'Neill; Abdul Rehman; Abhiram Maddukuri; Abhishek Gupta 004; Abhishek Padalkar; Abraham Lee; Acorn Pooley; Agrim Gupta; Ajay Mandlekar; Ajinkya Jain; Albert Tung; Alex Bewley; et al. (ICRA, 2024)

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Manon Devin; Alex X. Lee; Maria Bauzá Villalonga; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (Trans. Mach. Learn. Res., 2024)

Robot Data Curation with Mutual Information Estimators. - Joey Hejna; Suvir Mirchandani; Ashwin Balakrishna; Annie Xie; Ayzaan Wahid; Jonathan Tompson; Pannag Sanketi; Dhruv Shah; Coline Devin; Dorsa Sadigh (CoRR, 2025)

Gemini Robotics: Bringing AI into the Physical World. - Gemini Robotics Team; Saminda Abeyruwan; Joshua Ainslie; Jean-Baptiste Alayrac; Montserrat Gonzalez Arenas; Travis Armstrong; Ashwin Balakrishna; Robert Baruch; Maria Bauzá 001; Michiel Blokzijl; Steven Bohez; Konstantinos Bousmalis; et al. (CoRR, 2025)