Yoav Gelberg

According to our database, Yoav Gelberg authored at least 10 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

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

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

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Iterative Deployment Improves Planning Skills in LLMs.

Augusto B. Corrêa, Yoav Gelberg, Luckeciano C. Melo, Ilia Shumailov, André Grahl Pereira, Yarin Gal

CoRR, December, 2025

Extending the Context of Pretrained LLMs by Dropping Their Positional Embeddings.

Yoav Gelberg, Koshi Eguchi, Takuya Akiba, Edoardo Cetin

CoRR, December, 2025

On The Expressive Power of GNN Derivatives.

Yam Eitan, Moshe Eliasof, Yoav Gelberg, Fabrizio Frasca, Guy Bar-Shalom, Haggai Maron

CoRR, October, 2025

GradMetaNet: An Equivariant Architecture for Learning on Gradients.

Yoav Gelberg, Yam Eitan, Aviv Navon, Aviv Shamsian, Theo Putterman, Michael M. Bronstein, Haggai Maron

CoRR, July, 2025

Learning on LLM Output Signatures for gray-box LLM Behavior Analysis.

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

CoRR, March, 2025

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

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

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

Moe Putterman, Derek Lim, Yoav Gelberg, Stefanie Jegelka, Haggai Maron

CoRR, 2024

Topological Blind Spots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity.

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

CoRR, 2024

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

Yoav Gelberg, Tycho F. A. van der Ouderaa, Mark van der Wilk, Yarin Gal

Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024, 2024