Igor Gitman - RankMe

24 papers A* 3A 1Misc 1Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning Generative Selection for Best-of-N. CoRR Shubham Toshniwal, Aleksander Ficek, Siddhartha Jain, Wei Du, Vahid Noroozi, Sadegh Mahdavi, Somshubra Majumdar, Igor Gitman
2026	J	`jnl`	iGRPO: Self-Feedback-Driven LLM Reasoning. CoRR Ali Hatamizadeh, Shrimai Prabhumoye, Igor Gitman, Ximing Lu, Seungju Han, Wei Ping, Yejin Choi, Jan Kautz
2025	J	`jnl`	AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset. CoRR Ivan Moshkov, Darragh Hanley, Ivan Sorokin, Shubham Toshniwal, Christof Henkel, Benedikt Schifferer, Wei Du, Igor Gitman
2025	J	`jnl`	GenSelect: A Generative Approach to Best-of-N. CoRR Shubham Toshniwal, Ivan Sorokin, Aleksander Ficek, Ivan Moshkov, Igor Gitman
2025	—	`conf`	NeMo-Inspector: A Visualization Tool for LLM Generation Analysis. NAACL (System Demonstrations) Daria Gitman, Igor Gitman, Evelina Bakhturina
2025	J	`jnl`	NeMo-Inspector: A Visualization Tool for LLM Generation Analysis. CoRR Daria Gitman, Igor Gitman, Evelina Bakhturina
2025	J	`jnl`	Nemotron-Math: Efficient Long-Context Distillation of Mathematical Reasoning from Multi-Mode Supervision. CoRR Wei Du, Shubham Toshniwal, Branislav Kisacanin, Sadegh Mahdavi, Ivan Moshkov, George Armstrong, Stephen Ge, Edgar Minasyan, Feng Chen, Igor Gitman
2025	A*	`conf`	OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data. ICLR Shubham Toshniwal, Wei Du, Ivan Moshkov, Branislav Kisacanin, Alexan Ayrapetyan, Igor Gitman
2025	J	`jnl`	Scaling Generative Verifiers For Natural Language Mathematical Proof Verification And Selection. CoRR Sadegh Mahdavi, Branislav Kisacanin, Shubham Toshniwal, Wei Du, Ivan Moshkov, George Armstrong, Renjie Liao, Christos Thrampoulidis, Igor Gitman
2025	J	`jnl`	The Challenge of Teaching Reasoning to LLMs Without RL or Distillation. CoRR Wei Du, Branislav Kisacanin, George Armstrong, Shubham Toshniwal, Ivan Moshkov, Alexan Ayrapetyan, Sadegh Mahdavi, Dan Zhao, Shizhe Diao, Dragan Masulovic, Marius Stanean, Advaith Avadhanam, Max Wang, Ashmit Dutta, Shitij Govil, Sri Yanamandara, Mihir Tandon, Sriram Ananthakrishnan, Vedant Rathi, David Zhang, Joonseok Kang, Leon Luo, Titu Andreescu, Boris Ginsburg, Igor Gitman
2024	A*	`conf`	OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset. NeurIPS Shubham Toshniwal, Ivan Moshkov, Sean Narenthiran, Daria Gitman, Fei Jia, Igor Gitman
2024	J	`jnl`	OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset. CoRR Shubham Toshniwal, Ivan Moshkov, Sean Narenthiran, Daria Gitman, Fei Jia, Igor Gitman
2024	J	`jnl`	OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data. CoRR Shubham Toshniwal, Wei Du, Ivan Moshkov, Branislav Kisacanin, Alexan Ayrapetyan, Igor Gitman
2023	A	`conf`	Confidence-based Ensembles of End-to-End Speech Recognition Models. INTERSPEECH Igor Gitman, Vitaly Lavrukhin, Aleksandr Laptev, Boris Ginsburg
2023	J	`jnl`	Confidence-based Ensembles of End-to-End Speech Recognition Models. CoRR Igor Gitman, Vitaly Lavrukhin, Aleksandr Laptev, Boris Ginsburg
2023	J	`jnl`	Powerful and Extensible WFST Framework for RNN-Transducer Losses. CoRR Aleksandr Laptev, Vladimir Bataev, Igor Gitman, Boris Ginsburg
2023	Misc	`conf`	Powerful and Extensible WFST Framework for Rnn-Transducer Losses. ICASSP Aleksandr Laptev, Vladimir Bataev, Igor Gitman, Boris Ginsburg
2019	A*	`conf`	Understanding the Role of Momentum in Stochastic Gradient Methods. NeurIPS Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao
2019	J	`jnl`	Understanding the Role of Momentum in Stochastic Gradient Methods. CoRR Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao
2018	J	`jnl`	Convergence Analysis of Gradient Descent Algorithms with Proportional Updates. CoRR Igor Gitman, Deepak Dilipkumar, Ben Parr
2018	J	`jnl`	Novel Prediction Techniques Based on Clusterwise Linear Regression. CoRR Igor Gitman, Jieshi Chen, Eric Lei, Artur Dubrawski
2018	J	`jnl`	OpenSeq2Seq: extensible toolkit for distributed and mixed precision training of sequence-to-sequence models. CoRR Oleksii Kuchaiev, Boris Ginsburg, Igor Gitman, Vitaly Lavrukhin, Carl Case, Paulius Micikevicius
2017	J	`jnl`	Comparison of Batch Normalization and Weight Normalization Algorithms for the Large-scale Image Classification. CoRR Igor Gitman, Boris Ginsburg
2017	J	`jnl`	Scaling SGD Batch Size to 32K for ImageNet Training. CoRR Yang You, Igor Gitman, Boris Ginsburg