I'm a PhD student at Stanford.

I work on architectures and learning algorithms for language models, focusing on long-horizon tasks. I'm also interested in the structure of neural parameter spaces.

Rocky coastline and sea

selected papers

* equal contribution, full list on Google Scholar

  1. 2026

    Training Transformers for KV Cache Compressibility

    Yoav Gelberg*, Yam Eitan*, Michael Bronstein, Yarin Gal, Haggai Maron

    HiLD @ ICML 2026

  2. 2026

    Extending the Context of Pretrained LLMs by Dropping Their Positional Embeddings

    Yoav Gelberg, Koshi Eguchi, Takuya Akiva, Edoardo Cetin

    ICLR 2026, code, blog

  3. 2025

    GradMetaNet: An Equivariant Architecture for Learning on Gradients

    Yoav Gelberg*, Yam Eitan*, Aviv Navon, Aviv Shamsian, Theo (Moe) Putterman, Michael Bronstein, Haggai Maron

    NeurIPS 2025; Weight Space Learning Workshop @ ICLR 2025

  4. 2025

    Leaning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models

    Theo (Moe) Putterman*, Derek Lim*, Yoav Gelberg, Stephanie Jegelka, Haggai Maron

    LoG 2025, oral; Weight Space Learning Workshop @ ICLR 2025

  5. 2025

    Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions

    Fabrizio Frasca*, Guy Bar-Shalom*, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron

    AAAI 2026; R2-FM Workshop @ ICML 2025

  6. 2025

    Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity

    Yam Eitan*, Yoav Gelberg*, Guy Bar-Shalom, Fabrizio Frasca, Michael Bronstein, Haggai Maron

    ICLR 2025, oral, code

  7. 2024

    Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks

    Yoav Gelberg, Tycho van der Ouderaa, Mark van der Wilk, Yarin Gal

    GRaM Workshop @ ICML 2024, best paper