Max Ryabinin - RankMe

49 papers A* 16Journal 28Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Mashup Learning: Faster Finetuning by Remixing Past Checkpoints. CoRR Sofia Maria Lo Cicero Vaina, Artem Chumachenko, Max Ryabinin
2026	J	`jnl`	Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking. CoRR Ravi Ghadia, Maksim Abraham, Sergei Vorobyov, Max Ryabinin
2025	J	`jnl`	AutoJudge: Judge Decoding Without Manual Annotation. CoRR Roman Garipov, Fedor Velikonivtsev, Ruslan Svirschevski, Vage Egiazarian, Max Ryabinin
2025	A*	`conf`	Multilingual Language Model Pretraining using Machine-translated Data. EMNLP Jiayi Wang, Yao Lu, Maurice Weber, Max Ryabinin, David Ifeoluwa Adelani, Yihong Chen, Raphael Tang, Pontus Stenetorp
2025	J	`jnl`	Multilingual Language Model Pretraining using Machine-translated Data. CoRR Jiayi Wang, Yao Lu, Maurice Weber, Max Ryabinin, David Ifeoluwa Adelani, Yihong Chen, Raphael Tang, Pontus Stenetorp
2025	—	`conf`	Refined Assessment for Translation Evaluation: Rethinking Machine Translation Evaluation in the Era of Human-Level Systems. EMNLP (Findings) Dmitry Popov, Vladislav Negodin, Ekaterina Enikeeva, Iana Matrosova, Nikolay Karpachev, Max Ryabinin
2025	A*	`conf`	TOPLOC: A Locality Sensitive Hashing Scheme for Trustless Verifiable Inference. ICML Jack Min Ong, Matthew Di Ferrante, Aaron Pazdera, Ryan Garner, Sami Jaghouar, Manveer Basra, Max Ryabinin, Johannes Hagemann
2025	J	`jnl`	Towards Best Practices for Open Datasets for LLM Training. CoRR Stefan Baack, Stella Biderman, Kasia Odrozek, Aviya Skowron, Ayah Bdeir, Jillian Bommarito, Jennifer Ding, Maximilian Gahntz, Paul Keller, Pierre-Carl Langlais, Greg Lindahl, Sebastian Majstorovic, Nik Marda, Guilherme Penedo, Maarten Van Segbroeck, Jennifer Wang, Leandro von Werra, Mitchell Baker, Julie Belião, Kasia Chmielinski, Marzieh Fadaee, Lisa Gutermuth, Hynek Kydlícek, Greg Leppert, EM Lewis-Jong, Solana Larsen, Shayne Longpre, Angela Oduor Lungati, Cullen Miller, Victor Miller, Max Ryabinin, Kathleen Siminyu, Andrew Strait, Mark Surman, Anna Tumadóttir, Maurice Weber, Rebecca Weiss, Lee White, Thomas Wolf
2024	J	`jnl`	INTELLECT-1 Technical Report. CoRR Sami Jaghouar, Jack Min Ong, Manveer Basra, Fares Obeid, Jannik Straube, Michael Keiblinger, Elie Bakouch, Lucas Atkins, Maziyar Panahi, Charles Goddard, Max Ryabinin, Johannes Hagemann
2024	J	`jnl`	Label Privacy in Split Learning for Large Models with Parameter-Efficient Training. CoRR Philip Zmushko, Marat Mansurov, Ruslan Svirschevski, Denis Kuznedelev, Max Ryabinin, Aleksandr Beznosikov
2024	—	`conf`	Mind Your Format: Towards Consistent Evaluation of In-Context Learning Improvements. ACL (Findings) Anton Voronov, Lena Wolf, Max Ryabinin
2024	J	`jnl`	Mind Your Format: Towards Consistent Evaluation of In-Context Learning Improvements. CoRR Anton Voronov, Lena Wolf, Max Ryabinin
2024	J	`jnl`	Multilingual Pretraining Using a Large Corpus Machine-Translated from a Single Source Language. CoRR Jiayi Wang, Yao Lu, Maurice Weber, Max Ryabinin, Yihong Chen, Raphael Tang, Pontus Stenetorp
2024	A*	`conf`	RedPajama: an Open Dataset for Training Large Language Models. NeurIPS Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang
2024	J	`jnl`	RedPajama: an Open Dataset for Training Large Language Models. CoRR Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang
2024	A*	`conf`	Sequoia: Scalable and Robust Speculative Decoding. NeurIPS Zhuoming Chen, Avner May, Ruslan Svirschevski, Yuhsun Huang, Max Ryabinin, Zhihao Jia, Beidi Chen
2024	J	`jnl`	Sequoia: Scalable, Robust, and Hardware-aware Speculative Decoding. CoRR Zhuoming Chen, Avner May, Ruslan Svirschevski, Yuhsun Huang, Max Ryabinin, Zhihao Jia, Beidi Chen
2024	A*	`conf`	SpecExec: Massively Parallel Speculative Decoding For Interactive LLM Inference on Consumer Devices. NeurIPS Ruslan Svirschevski, Avner May, Zhuoming Chen, Beidi Chen, Zhihao Jia, Max Ryabinin
2024	J	`jnl`	SpecExec: Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices. CoRR Ruslan Svirschevski, Avner May, Zhuoming Chen, Beidi Chen, Zhihao Jia, Max Ryabinin
2024	J	`jnl`	The Hallucinations Leaderboard - An Open Effort to Measure Hallucinations in Large Language Models. CoRR Giwon Hong, Aryo Pradipta Gema, Rohit Saxena, Xiaotang Du, Ping Nie, Yu Zhao, Laura Perez-Beltrachini, Max Ryabinin, Xuanli He, Clémentine Fourrier, Pasquale Minervini
2023	A*	`conf`	Distributed Inference and Fine-tuning of Large Language Models Over The Internet. NeurIPS Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin A. Raffel
2023	J	`jnl`	Distributed Inference and Fine-tuning of Large Language Models Over The Internet. CoRR Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin Raffel
2023	A*	`conf`	FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. ICML Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang
2023	J	`jnl`	High-throughput Generative Inference of Large Language Models with a Single GPU. CoRR Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y. Fu, Zhiqiang Xie, Beidi Chen, Clark W. Barrett, Joseph E. Gonzalez, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang
2023	J	`jnl`	Hypernymy Understanding Evaluation of Text-to-Image Models via WordNet Hierarchy. CoRR Anton Baryshnikov, Max Ryabinin
2023	A*	`conf`	Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics. NeurIPS Anton Voronov, Mikhail Khoroshikh, Artem Babenko, Max Ryabinin
2023	J	`jnl`	Is This Loss Informative? Speeding Up Textual Inversion with Deterministic Objective Evaluation. CoRR Anton Voronov, Mikhail Khoroshikh, Artem Babenko, Max Ryabinin
2023	A*	`conf`	SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient. ICML Max Ryabinin, Tim Dettmers, Michael Diskin, Alexander Borzunov
2023	J	`jnl`	SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient. CoRR Max Ryabinin, Tim Dettmers, Michael Diskin, Alexander Borzunov
2022	A*	`conf`	Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees. NeurIPS Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander V. Gasnikov
2022	J	`jnl`	Petals: Collaborative Inference and Fine-tuning of Large Models. CoRR Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers, Max Ryabinin, Younes Belkada, Artem Chumachenko, Pavel Samygin, Colin Raffel
2022	A*	`conf`	RuCoLA: Russian Corpus of Linguistic Acceptability. EMNLP Vladislav Mikhailov, Tatiana Shamardina, Max Ryabinin, Alena Pestova, Ivan Smurov, Ekaterina Artemova
2022	J	`jnl`	RuCoLA: Russian Corpus of Linguistic Acceptability. CoRR Vladislav Mikhailov, Tatiana Shamardina, Max Ryabinin, Alena Pestova, Ivan Smurov, Ekaterina Artemova
2022	A*	`conf`	Secure Distributed Training at Scale. ICML Eduard Gorbunov, Alexander Borzunov, Michael Diskin, Max Ryabinin
2022	J	`jnl`	Training Transformers Together. CoRR Alexander Borzunov, Max Ryabinin, Tim Dettmers, Quentin Lhoest, Lucile Saulnier, Michael Diskin, Yacine Jernite, Thomas Wolf
2021	A*	`conf`	Distributed Deep Learning In Open Collaborations. NeurIPS Michael Diskin, Alexey Bukhtiyarov, Max Ryabinin, Lucile Saulnier, Quentin Lhoest, Anton Sinitsin, Dmitry Popov, Dmitry V. Pyrkin, Maxim Kashirin, Alexander Borzunov, Albert Villanova del Moral, Denis Mazur, Ilia Kobelev, Yacine Jernite, Thomas Wolf, Gennady Pekhimenko
2021	J	`jnl`	Distributed Deep Learning in Open Collaborations. CoRR Michael Diskin, Alexey Bukhtiyarov, Max Ryabinin, Lucile Saulnier, Quentin Lhoest, Anton Sinitsin, Dmitry Popov, Dmitry V. Pyrkin, Maxim Kashirin, Alexander Borzunov, Albert Villanova del Moral, Denis Mazur, Ilia Kobelev, Yacine Jernite, Thomas Wolf, Gennady Pekhimenko
2021	J	`jnl`	Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees. CoRR Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander V. Gasnikov
2021	—	`conf`	It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense Reasoning. ACL/IJCNLP (Findings) Alexey Tikhonov, Max Ryabinin
2021	J	`jnl`	It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense Reasoning. CoRR Alexey Tikhonov, Max Ryabinin
2021	A*	`conf`	Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices. NeurIPS Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko
2021	J	`jnl`	Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices. CoRR Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko
2021	A*	`conf`	Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets. NeurIPS Max Ryabinin, Andrey Malinin, Mark J. F. Gales
2021	J	`jnl`	Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets. CoRR Max Ryabinin, Andrey Malinin, Mark J. F. Gales
2021	J	`jnl`	Secure Distributed Training at Scale. CoRR Eduard Gorbunov, Alexander Borzunov, Michael Diskin, Max Ryabinin
2021	—	`conf`	Training Transformers Together. NeurIPS (Competition and Demos) Alexander Borzunov, Max Ryabinin, Tim Dettmers, Quentin Lhoest, Lucile Saulnier, Michael Diskin, Yacine Jernite, Thomas Wolf
2020	—	`conf`	Embedding Words in Non-Vector Space with Unsupervised Graph Learning. EMNLP (1) Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita
2020	J	`jnl`	Embedding Words in Non-Vector Space with Unsupervised Graph Learning. CoRR Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita
2020	A*	`conf`	Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts. NeurIPS Max Ryabinin, Anton Gusev