Accelerating SGD for Distributed Deep-Learning Using an Approximted Hessian Matrix. - Sébastien M. R. Arnold; Chunming Wang (ICLR (Workshop), 2017)

Accelerating SGD for Distributed Deep-Learning Using Approximated Hessian Matrix. - Sébastien M. R. Arnold; Chunming Wang (CoRR, 2017)

Shapechanger: Environments for Transfer Learning. - Sébastien M. R. Arnold; Tsam Kiu Pun; Théo-Tim J. Denisart; Francisco J. Valero Cuevas (CoRR, 2017)

Reducing the variance in online optimization by transporting past gradients. - Sébastien M. R. Arnold; Pierre-Antoine Manzagol; Reza Babanezhad 001; Ioannis Mitliagkas; Nicolas Le Roux (NeurIPS, 2019)

Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator. - James A. Preiss; Sébastien M. R. Arnold; Chen-Yu Wei; Marius Kloft (CoRR, 2019)

Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning. - Sébastien M. R. Arnold; Shariq Iqbal; Fei Sha (CoRR, 2019)

learn2learn: A Library for Meta-Learning Research. - Sébastien M. R. Arnold; Praateek Mahajan; Debajyoti Datta; Ian Bunner; Konstantinos Saitas Zarkias (CoRR, 2020)

When MAML Can Adapt Fast and How to Assist When It Cannot. - Sébastien M. R. Arnold; Shariq Iqbal; Fei Sha (AISTATS, 2021)

Uniform Sampling over Episode Difficulty. - Sébastien M. R. Arnold; Guneet S. Dhillon; Avinash Ravichandran; Stefano Soatto (NeurIPS, 2021)

Embedding Adaptation is Still Needed for Few-Shot Learning. - Sébastien M. R. Arnold; Fei Sha (CoRR, 2021)

Policy Learning and Evaluation with Randomized Quasi-Monte Carlo. - Sébastien M. R. Arnold; Pierre L'Ecuyer; Liyu Chen; Yi-Fan Chen; Fei Sha (AISTATS, 2022)

RoboCLIP: One Demonstration is Enough to Learn Robot Policies. - Sumedh Sontakke; Jesse Zhang; Sébastien M. R. Arnold; Karl Pertsch; Erdem Biyik; Dorsa Sadigh; Chelsea Finn; Laurent Itti (NeurIPS, 2023)

Policy-Induced Self-Supervision Improves Representation Finetuning in Visual RL. - Sébastien M. R. Arnold; Fei Sha (CoRR, 2023)

A domain-agnostic approach for characterization of lifelong learning systems. - 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; et al. (Neural Networks, 2023)

Can an LLM-Powered Socially Assistive Robot Effectively and Safely Deliver Cognitive Behavioral Therapy? A Study With University Students. - 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; et al. (CoRR, 2024)

Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? - 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 008; et al. (CoRR, 2024)

Using Linguistic Entrainment to Evaluate Large Language Models for Use in Cognitive Behavioral Therapy. - Mina J. Kian; Kaleen Shrestha; Katrin Fischer; Xiaoyuan Zhu; Jonathan Ong; Aryan Trehan; Jessica Wang; Gloria Chang; Sébastien M. R. Arnold; Maja J. Mataric (NAACL (Findings), 2025)

LOFT: Scalable and More Realistic Long-Context Evaluation. - 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 008; et al. (NAACL (Findings), 2025)

Graders should cheat: privileged information enables expert-level automated evaluations. - Jin Peng Zhou; Sébastien M. R. Arnold; Nan Ding 002; Kilian Q. Weinberger; Nan Hua; Fei Sha (CoRR, 2025)

Engagement and Disclosures in LLM-Powered Cognitive Behavioral Therapy Exercises: A Factorial Design Comparing the Influence of a Robot vs. Chatbot Over Time. - 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; et al. (CoRR, 2025)