Sébastien M. R. Arnold

27 papers A* 4A 2B 1Journal 17Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	Engagement and Disclosures in LLM-Powered Cognitive Behavioral Therapy Exercises: A Factorial Design Comparing the Influence of a Robot vs. Chatbot Over Time. RO-MAN Mina J. Kian, Mingyu Zong, Katrin Fischer, Anna-Maria Velentza, Abhyuday Singh, Kaleen Shrestha, Pau Sang, Shriya Upadhyay, Wallace Browning, Misha A. Faruki, Sébastien M. R. Arnold, Bhaskar Krishnamachari, Maja J. Mataric
2025	J	`jnl`	Engagement and Disclosures in LLM-Powered Cognitive Behavioral Therapy Exercises: A Factorial Design Comparing the Influence of a Robot vs. Chatbot Over Time. CoRR Mina J. Kian, Mingyu Zong, Katrin Fischer, Anna-Maria Velentza, Abhyuday Singh, Kaleen Shrestha, Pau Sang, Shriya Upadhyay, Wallace Browning, Misha A. Faruki, Sébastien M. R. Arnold, Bhaskar Krishnamachari, Maja J. Mataric
2025	A*	`conf`	Graders Should Cheat: Privileged Information Enables Expert-Level Automated Evaluations. EMNLP Jin Peng Zhou, Sébastien M. R. Arnold, Nan Ding, Kilian Q. Weinberger, Nan Hua, Fei Sha
2025	J	`jnl`	Graders should cheat: privileged information enables expert-level automated evaluations. CoRR Jin Peng Zhou, Sébastien M. R. Arnold, Nan Ding, Kilian Q. Weinberger, Nan Hua, Fei Sha
2025	—	`conf`	LOFT: Scalable and More Realistic Long-Context Evaluation. NAACL (Findings) Jinhyuk Lee, Anthony Chen, Zhuyun Dai, Dheeru Dua, Devendra Singh Sachan, Michael Boratko, Yi Luan, Sébastien M. R. Arnold, Vincent Perot, Siddharth Dalmia, Hexiang Hu, Xudong Lin, Panupong Pasupat, Aida Amini, Jeremy R. Cole, Sebastian Riedel, Iftekhar Naim, Ming-Wei Chang, Kelvin Guu
2025	—	`conf`	Using Linguistic Entrainment to Evaluate Large Language Models for Use in Cognitive Behavioral Therapy. NAACL (Findings) Mina J. Kian, Kaleen Shrestha, Katrin Fischer, Xiaoyuan Zhu, Jonathan Ong, Aryan Trehan, Jessica Wang, Gloria Chang, Sébastien M. R. Arnold, Maja J. Mataric
2024	J	`jnl`	Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? CoRR Jinhyuk Lee, Anthony Chen, Zhuyun Dai, Dheeru Dua, Devendra Singh Sachan, Michael Boratko, Yi Luan, Sébastien M. R. Arnold, Vincent Perot, Siddharth Dalmia, Hexiang Hu, Xudong Lin, Panupong Pasupat, Aida Amini, Jeremy R. Cole, Sebastian Riedel, Iftekhar Naim, Ming-Wei Chang, Kelvin Guu
2024	J	`jnl`	Can an LLM-Powered Socially Assistive Robot Effectively and Safely Deliver Cognitive Behavioral Therapy? A Study With University Students. CoRR Mina J. Kian, Mingyu Zong, Katrin Fischer, Abhyuday Singh, Anna-Maria Velentza, Pau Sang, Shriya Upadhyay, Anika Gupta, Misha A. Faruki, Wallace Browning, Sébastien M. R. Arnold, Bhaskar Krishnamachari, Maja J. Mataric
2023	J	`jnl`	A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Dimitri Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha
2023	J	`jnl`	A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha
2023	J	`jnl`	Policy-Induced Self-Supervision Improves Representation Finetuning in Visual RL. CoRR Sébastien M. R. Arnold, Fei Sha
2023	A*	`conf`	RoboCLIP: One Demonstration is Enough to Learn Robot Policies. NeurIPS Sumedh Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti
2023	J	`jnl`	RoboCLIP: One Demonstration is Enough to Learn Robot Policies. CoRR Sumedh A. Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti
2022	A	`conf`	Policy Learning and Evaluation with Randomized Quasi-Monte Carlo. AISTATS Sébastien M. R. Arnold, Pierre L'Ecuyer, Liyu Chen, Yi-Fan Chen, Fei Sha
2022	J	`jnl`	Policy Learning and Evaluation with Randomized Quasi-Monte Carlo. CoRR Sébastien M. R. Arnold, Pierre L'Ecuyer, Liyu Chen, Yi-Fan Chen, Fei Sha
2021	J	`jnl`	Embedding Adaptation is Still Needed for Few-Shot Learning. CoRR Sébastien M. R. Arnold, Fei Sha
2021	A*	`conf`	Uniform Sampling over Episode Difficulty. NeurIPS Sébastien M. R. Arnold, Guneet S. Dhillon, Avinash Ravichandran, Stefano Soatto
2021	J	`jnl`	Uniform Sampling over Episode Difficulty. CoRR Sébastien M. R. Arnold, Guneet S. Dhillon, Avinash Ravichandran, Stefano Soatto
2021	A	`conf`	When MAML Can Adapt Fast and How to Assist When It Cannot. AISTATS Sébastien M. R. Arnold, Shariq Iqbal, Fei Sha
2020	J	`jnl`	learn2learn: A Library for Meta-Learning Research. CoRR Sébastien M. R. Arnold, Praateek Mahajan, Debajyoti Datta, Ian Bunner, Konstantinos Saitas Zarkias
2019	J	`jnl`	Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator. CoRR James A. Preiss, Sébastien M. R. Arnold, Chen-Yu Wei, Marius Kloft
2019	J	`jnl`	Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning. CoRR Sébastien M. R. Arnold, Shariq Iqbal, Fei Sha
2019	A*	`conf`	Reducing the variance in online optimization by transporting past gradients. NeurIPS Sébastien M. R. Arnold, Pierre-Antoine Manzagol, Reza Babanezhad, Ioannis Mitliagkas, Nicolas Le Roux
2019	J	`jnl`	Reducing the variance in online optimization by transporting past gradients. CoRR Sébastien M. R. Arnold, Pierre-Antoine Manzagol, Reza Babanezhad, Ioannis Mitliagkas, Nicolas Le Roux
2017	J	`jnl`	Accelerating SGD for Distributed Deep-Learning Using Approximated Hessian Matrix. CoRR Sébastien M. R. Arnold, Chunming Wang
2017	—	`conf`	Accelerating SGD for Distributed Deep-Learning Using an Approximted Hessian Matrix. ICLR (Workshop) Sébastien M. R. Arnold, Chunming Wang
2017	J	`jnl`	Shapechanger: Environments for Transfer Learning. CoRR Sébastien M. R. Arnold, Tsam Kiu Pun, Théo-Tim J. Denisart, Francisco J. Valero Cuevas