Ido Galil

According to our database, Ido Galil authored at least 13 papers between 2021 and 2026.

Collaborative distances:

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

2026

Extending Puzzle for Mixture-of-Experts Reasoning Models with Application to GPT-OSS Acceleration.

Akhiad Bercovich, Nir Ailon, Vladimir Anisimov, Tomer Asida, Nave Assaf, Mohammad Dabbah, Ido Galil, Amnon Geifman, Yonatan Geifman, Izhak Golan, Roi Koren, Itay Levy, Zach Moshe, Pavlo Molchanov, Najeeb Nabwani, Mostofa Patwari, Omri Puny, Tomer Ronen, Itamar Schen, Elad Segal, Ido Shahaf, Oren Tropp, Ran Zilberstein, Ran El-Yaniv

CoRR, February, 2026

When Should LLMs Be Less Specific? Selective Abstraction for Reliable Long-Form Text Generation.

Shani Goren, Ido Galil, Ran El-Yaniv

CoRR, February, 2026

Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips.

Ido Galil, Moshe Kimhi, Ran El-Yaniv

Trans. Mach. Learn. Res., 2026

2025

FFN Fusion: Rethinking Sequential Computation in Large Language Models.

Akhiad Bercovich, Mohammad Dabbah, Omri Puny, Ido Galil, Amnon Geifman, Yonatan Geifman, Izhak Golan, Ehud Karpas, Itay Levy, Zach Moshe, Najeeb Nabwani, Tomer Ronen, Itamar Schen, Elad Segal, Ido Shahaf, Oren Tropp, Ran Zilberstein, Ran El-Yaniv

CoRR, March, 2025

No Data, No Optimization: A Lightweight Method To Disrupt Neural Networks With Sign-Flips.

Ido Galil, Moshe Kimhi, Ran El-Yaniv

CoRR, February, 2025

FFN Fusion: Rethinking Sequential Computation in Large Language Models.

Akhiad Bercovich, Mohammad Dabbah, Omri Puny, Ido Galil, Amnon Geifman, Yonatan Geifman, Izik Golan, Ehud Karpas, Itay Levy, Zach Moshe, Najeeb Nabwani, Tomer Ronen, Itamar Schen, Ido Shahaf, Oren Tropp, Ran Zilberstein, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models.

Michael Toker, Ido Galil, Hadas Orgad, Rinon Gal, Yoad Tewel, Gal Chechik, Yonatan Belinkov

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Puzzle: Distillation-Based NAS for Inference-Optimized LLMs.

Akhiad Bercovich, Tomer Ronen, Talor Abramovich, Nir Ailon, Nave Assaf, Mohammad Dabbah, Ido Galil, Amnon Geifman, Yonatan Geifman, Izhak Golan, Netanel Haber, Ehud Karpas, Roi Koren, Itay Levy, Pavlo Molchanov, Shahar Mor, Zach Moshe, Najeeb Nabwani, Omri Puny, Ran Rubin, Itamar Schen, Ido Shahaf, Oren Tropp, Omer Ullman Argov, Ran Zilberstein, Ran El-Yaniv

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Hierarchical Selective Classification.

Shani Goren, Ido Galil, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

What Can we Learn From The Selective Prediction And Uncertainty Estimation Performance Of 523 Imagenet Classifiers?

Ido Galil, Mohammed Dabbah, Ran El-Yaniv

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A framework for benchmarking Class-out-of-distribution detection and its application to ImageNet.

Ido Galil, Mohammed Dabbah, Ran El-Yaniv

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Which models are innately best at uncertainty estimation?

Ido Galil, Mohammed Dabbah, Ran El-Yaniv

CoRR, 2022

2021

Disrupting Deep Uncertainty Estimation Without Harming Accuracy.

Ido Galil, Ran El-Yaniv

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021