Preprints

  • Did I Faithfully Say What I Thought? Bridging the Gap Between Neural Activity and Self-Explanations in Large Language Models
    , Jean-Noel Vittaut, Nicolas Chesneau, , and Marie-Jeanne Lesot
    In ArXiv, 2025.
    #NLP
    [arXiv]

  • V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
    Mahmoud Assran*, Adrien Bardes*, David Fan*, Quentin Garrido*, Russell Howes*, Mojtaba Komeili*, Matthew Muckley*, Ammar Rizvi*, Claire Roberts*, Koustuv Sinha*, , Sergio Arnaud*, Abha Gejji*, Ada Martin*, Francois Robert Hogan*, Daniel Dugas*, Piotr Bojanowski, Vasil Khalidov, Patrick Labatut, Francisco Massa, Marc Szafraniec, Kapil Krishnakumar, Yong Li, Xiaodong Ma, , Franziska Meier*, Yann LeCun*, Michael Rabbat*, and Nicolas Ballas*
    Technical Report, 2025.
    #DL
    [website], [arXiv], [code], [huggingface], [blogpost]

  • Boosting LLM Reasoning via Spontaneous Self-Correction
    , Tengyu Xu, Xuewei Wang, Zhengxing Chen, Di Jin, Liang Tan, Yen-Ting, Zishun Yu, Zhuokai Zhao, Yun He, Sinong Wang, Han Fang, , and Chen Zhu
    In ArXiv, 2025.
    #NLP, #RL
    [arXiv]

  • Steering Large Language Model Activations in Sparse Spaces
    Reza Bayat, , Mohammad Pezeshki, , and Pascal Vincent
    In ArXiv, 2025.
    #NLP, #DL
    [arXiv]

  • Torque-Aware Momentum
    , , Aristide Baratin, Reza Babanezhad Harikandeh, Gintare Karolina Dziugaite, Razvan Pascanu, and
    In ArXiv, 2024.
    #DL
    [arXiv]

  • TRecViT: A Recurrent Video Transformer
    Viorica Pătrăucean, Xu Owen He, Joseph Heyward, Chuhan Zhang, Mehdi S. M. Sajjadi, George-Cristian Muraru, , Mahdi Karami, Ross Goroshin, Yutian Chen, Simon Osindero, João Carreira, and Razvan Pascanu
    In ArXiv, 2024.
    #DL
    [arXiv]

  • Too Big to Fool: Resisting Deception in Language Models
    , Mats Leon Richter, Juan Rodriguez, , , and Maxime Gasse
    In ArXiv, 2024.
    #NLP
    [arXiv]

  • Unraveling the Complexity of Memory in RL Agents: An Approach for Classification and Evaluation
    Egor Cherepanov, Nikita Kachaev, , Alexey K. Kovalev, and Aleksandr I. Panov
    In ArXiv, 2024.
    #RL
    [arXiv]

  • Interpretability Needs a New Paradigm
    , Himabindu Lakkaraju, Siva Reddy, and
    In ArXiv, 2024.
    #NLP, #DL
    [arXiv]

  • Protein Language Models: Is Scaling Necessary?
    , Robert M. Vernon, Almer van der Sloot, Benjamin Schulz, , and Christopher James Langmead
    In bioRxiv, 2024.
    #DL, #Other
    [bioRxiv], [code]

  • Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent
    Karolis Jucys, George Adamopoulos, Mehrab Hamidi, Stephanie Milani, , , Sonia Joseph, Blake Richards, Irina Rish, and Özgür Şimşek
    Mechanistic Interpretability Workshop, ICML, 2024.
    #Other
    [arXiv]

  • Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?
    , Anne Kerbrat, Pierre Labauge, Tobias Granberg, Jason Talbott, Daniel S. Reich, Massimo Filippi, Rohit Bakshi, Virginie Callot, , and Julien Cohen-Adad
    In ArXiv, 2022.
    [Medical Imaging meets NeurIPS Workshop, 2022]
    #DL
    [arXiv], [code]

  • Feature diversity in self-supervised learning
    and
    Conference on Lifelong Learning Agents (CoLLAs) Workshop Track, 2022.
    #DL
    [arXiv]

  • An Introduction to Lifelong Supervised Learning
    Shagun Sodhani, Mojtaba Farmazi, Sanket Vaibhav Mehta, , , , and
    In ArXiv, 2022.
    #DL
    [arXiv]

  • Maximum Reward Formulation In Reinforcement Learning
    Sai Krishna Gottipati, Yashaswi Pathak, Rohan Nuttall, Raviteja Chunduru, Ahmed Touati, Sriram Ganapathi Subramanian, Matthew E Taylor, and
    In arXiv, 2020.
    #RL
    [arXiv]