papershelf

Papers I am reading or finding interesting.

RL

  1. arXiv
    floq: Training Critics via Flow-Matching for Scaling Compute in Value-Based RL
    Bhavya Agrawalla, Michal Nauman, Khush Agrawal, and 1 more author
    arXiv preprint arXiv:2509.06863, 2025
    DOI HTML
  2. ICML
    Learning Latent Dynamics for Planning from Pixels
    Danijar Hafner, Timothy Lillicrap, Ian Fischer, and 4 more authors
    In International Conference on Machine Learning (ICML), 2019
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CV

  1. CVPR
    Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
    Mahmoud Assran, Quentin Duval, Ishan Misra, and 5 more authors
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
    DOI HTML
  2. arXiv
    LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
    Randall Balestriero and Yann LeCun
    arXiv preprint arXiv:2511.08544, 2025
    DOI HTML

NLP

  1. SSRN
    On the Slow Death of Scaling
    Sara Hooker
    SSRN, Dec 2025
    DOI HTML
  2. NAACL
    BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
    Jacob Devlin, Ming-Wei Chang, Kenton Lee, and 1 more author
    In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), 2019
    DOI HTML

Psychology

  1. Cognition
    If it’s important, then I am curious: A value intervention to induce curiosity
    Rachit Dubey, Thomas L Griffiths, and Tania Lombrozo
    Cognition, 2022
    DOI HTML
  2. TiCS
    Constructing language: a framework for explaining acquisition
    Caroline F. Rowland, Gert Westermann, Anna L. Theakston, and 3 more authors
    Trends in Cognitive Sciences, 2025
    DOI HTML
  3. TiCS
    Searching for the Goldilocks zone of climate anxiety
    Alexandre Heeren and Susan Clayton
    Trends in Cognitive Sciences, 2026
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Others

  1. JSTOR
    The Mundanity of Excellence: An Ethnographic Report on Stratification and Olympic Swimmers
    Daniel F. Chambliss
    Sociological Theory, 1989
    DOI HTML