Ido Hakimi - RankMe

24 papers A* 8B 1Journal 13Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ActiveUltraFeedback: Efficient Preference Data Generation using Active Learning. CoRR Davit Melikidze, Marian Schneider, Jessica Lam, Martin Wertich, Ido Hakimi, Barna Pásztor, Andreas Krause
2026	J	`jnl`	Reinforcement Learning via Self-Distillation. CoRR Jonas Hübotter, Frederike Lübeck, Lejs Behric, Anton Baumann, Marco Bagatella, Daniel Marta, Ido Hakimi, Idan Shenfeld, Thomas Kleine Buening, Carlos Guestrin, Andreas Krause
2026	J	`jnl`	RewardUQ: A Unified Framework for Uncertainty-Aware Reward Models. CoRR Daniel Yang, Samuel Stante, Florian Redhardt, Lena Libon, Parnian Kassraie, Ido Hakimi, Barna Pásztor, Andreas Krause
2025	A*	`conf`	Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs. ICLR Jonas Hübotter, Sascha Bongni, Ido Hakimi, Andreas Krause
2025	A*	`conf`	From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning. EMNLP David Dinucu-Jianu, Jakub Macina, Nico Daheim, Ido Hakimi, Iryna Gurevych, Mrinmaya Sachan
2025	J	`jnl`	From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning. CoRR David Dinucu-Jianu, Jakub Macina, Nico Daheim, Ido Hakimi, Iryna Gurevych, Mrinmaya Sachan
2025	J	`jnl`	Learning on the Job: Test-Time Curricula for Targeted Reinforcement Learning. CoRR Jonas Hübotter, Leander Diaz-Bone, Ido Hakimi, Andreas Krause, Moritz Hardt
2025	J	`jnl`	Local Mixtures of Experts: Essentially Free Test-Time Training via Model Merging. CoRR Ryo Bertolissi, Jonas Hübotter, Ido Hakimi, Andreas Krause
2025	A*	`conf`	MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors. EMNLP Jakub Macina, Nico Daheim, Ido Hakimi, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan
2025	J	`jnl`	MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors. CoRR Jakub Macina, Nico Daheim, Ido Hakimi, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan
2025	J	`jnl`	Maximizing Prefix-Confidence at Test-Time Efficiently Improves Mathematical Reasoning. CoRR Matthias Otth, Jonas Hübotter, Ido Hakimi, Andreas Krause
2024	J	`jnl`	Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs. CoRR Jonas Hübotter, Sascha Bongni, Ido Hakimi, Andreas Krause
2023	A*	`conf`	q2d: Turning Questions into Dialogs to Teach Models How to Search. EMNLP Yonatan Bitton, Shlomi Cohen-Ganor, Ido Hakimi, Yoad Lewenberg, Roee Aharoni, Enav Weinreb
2023	J	`jnl`	q2d: Turning Questions into Dialogs to Teach Models How to Search. CoRR Yonatan Bitton, Shlomi Cohen-Ganor, Ido Hakimi, Yoad Lewenberg, Roee Aharoni, Enav Weinreb
2022	—	`—`	Distributed Deep Neural Networks. Ido Hakimi
2022	B	`conf`	SMEGA2: Distributed Asynchronous Deep Neural Network Training With a Single Momentum Buffer. ICPP Refael Cohen, Ido Hakimi, Assaf Schuster
2021	A*	`conf`	Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior Knowledge. ICML Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Yehuda Levy
2021	A*	`conf`	Faster Neural Network Training with Approximate Tensor Operations. NeurIPS Menachem Adelman, Kfir Y. Levy, Ido Hakimi, Mark Silberstein
2021	—	`conf`	Fine-tuning giant neural networks on commodity hardware with automatic pipeline model parallelism. USENIX ATC Saar Eliad, Ido Hakimi, Alon De Jagger, Mark Silberstein, Assaf Schuster
2021	A*	`conf`	LAGA: Lagged AllReduce with Gradient Accumulation for Minimal Idle Time. ICDM Ido Hakimi, Rotem Zamir Aviv, Kfir Y. Levy, Assaf Schuster
2021	J	`jnl`	Learning Under Delayed Feedback: Implicitly Adapting to Gradient Delays. CoRR Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Y. Levy
2020	A*	`conf`	Gap-Aware Mitigation of Gradient Staleness. ICLR Saar Barkai, Ido Hakimi, Assaf Schuster
2019	J	`jnl`	Gap Aware Mitigation of Gradient Staleness. CoRR Saar Barkai, Ido Hakimi, Assaf Schuster
2019	J	`jnl`	Taming Momentum in a Distributed Asynchronous Environment. CoRR Ido Hakimi, Saar Barkai, Moshe Gabel, Assaf Schuster