Ido Galil

18 papers A* 5Journal 12Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Extending Puzzle for Mixture-of-Experts Reasoning Models with Application to GPT-OSS Acceleration.
CoRR
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
2026 J jnl
Maximal Brain Damage Without Data or Optimization: Disrupting Neural Networks via Sign-Bit Flips.
Trans. Mach. Learn. Res.
Ido Galil, Moshe Kimhi, Ran El-Yaniv
2026 J jnl
When Should LLMs Be Less Specific? Selective Abstraction for Reliable Long-Form Text Generation.
CoRR
Shani Goren, Ido Galil, Ran El-Yaniv
2025 J jnl
FFN Fusion: Rethinking Sequential Computation in Large Language Models.
CoRR
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
2025 J jnl
No Data, No Optimization: A Lightweight Method To Disrupt Neural Networks With Sign-Flips.
CoRR
Ido Galil, Moshe Kimhi, Ran El-Yaniv
2025 — conf
Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models.
NAACL (Long Papers)
Michael Toker, Ido Galil, Hadas Orgad, Rinon Gal, Yoad Tewel, Gal Chechik, Yonatan Belinkov
2025 J jnl
Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models.
CoRR
Michael Toker, Ido Galil, Hadas Orgad, Rinon Gal, Yoad Tewel, Gal Chechik, Yonatan Belinkov
2025 A* conf
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs.
ICML
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
2024 A* conf
Hierarchical Selective Classification.
NeurIPS
Shani Goren, Ido Galil, Ran El-Yaniv
2024 J jnl
Hierarchical Selective Classification.
CoRR
Shani Goren, Ido Galil, Ran El-Yaniv
2024 J jnl
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs.
CoRR
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
2023 A* conf
A framework for benchmarking Class-out-of-distribution detection and its application to ImageNet.
ICLR
Ido Galil, Mohammed Dabbah, Ran El-Yaniv
2023 J jnl
A framework for benchmarking class-out-of-distribution detection and its application to ImageNet.
CoRR
Ido Galil, Mohammed Dabbah, Ran El-Yaniv
2023 J jnl
What Can We Learn From The Selective Prediction And Uncertainty Estimation Performance Of 523 Imagenet Classifiers.
CoRR
Ido Galil, Mohammed Dabbah, Ran El-Yaniv
2023 A* conf
What Can we Learn From The Selective Prediction And Uncertainty Estimation Performance Of 523 Imagenet Classifiers?
ICLR
Ido Galil, Mohammed Dabbah, Ran El-Yaniv
2022 J jnl
Which models are innately best at uncertainty estimation?
CoRR
Ido Galil, Mohammed Dabbah, Ran El-Yaniv
2021 A* conf
Disrupting Deep Uncertainty Estimation Without Harming Accuracy.
NeurIPS
Ido Galil, Ran El-Yaniv
2021 J jnl
Disrupting Deep Uncertainty Estimation Without Harming Accuracy.
CoRR
Ido Galil, Ran El-Yaniv