Max Ryabinin

According to our database, Max Ryabinin authored at least 23 papers between 2020 and 2024.

Collaborative distances:

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

2024

Multilingual Pretraining Using a Large Corpus Machine-Translated from a Single Source Language.

Jiayi Wang, Yao Lu, Maurice Weber, Max Ryabinin, Yihong Chen, Raphael Tang, Pontus Stenetorp

CoRR, 2024

SpecExec: Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices.

Ruslan Svirschevski, Avner May, Zhuoming Chen, Beidi Chen, Zhihao Jia, Max Ryabinin

CoRR, 2024

The Hallucinations Leaderboard - An Open Effort to Measure Hallucinations in Large Language Models.

Giwon Hong, Aryo Pradipta Gema, Rohit Saxena, Xiaotang Du, Ping Nie, Yu Zhao, Laura Perez-Beltrachini, Max Ryabinin, Xuanli He, Clémentine Fourrier, Pasquale Minervini

CoRR, 2024

Sequoia: Scalable, Robust, and Hardware-aware Speculative Decoding.

Zhuoming Chen, Avner May, Ruslan Svirschevski, Yuhsun Huang, Max Ryabinin, Zhihao Jia, Beidi Chen

CoRR, 2024

Mind Your Format: Towards Consistent Evaluation of In-Context Learning Improvements.

Anton Voronov, Lena Wolf, Max Ryabinin

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Hypernymy Understanding Evaluation of Text-to-Image Models via WordNet Hierarchy.

Anton Baryshnikov, Max Ryabinin

CoRR, 2023

High-throughput Generative Inference of Large Language Models with a Single GPU.

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

CoRR, 2023

Is This Loss Informative? Speeding Up Textual Inversion with Deterministic Objective Evaluation.

Anton Voronov, Mikhail Khoroshikh, Artem Babenko, Max Ryabinin

CoRR, 2023

Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics.

Anton Voronov, Mikhail Khoroshikh, Artem Babenko, Max Ryabinin

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distributed Inference and Fine-tuning of Large Language Models Over The Internet.

Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin A. Raffel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient.

Max Ryabinin, Tim Dettmers, Michael Diskin, Alexander Borzunov

Proceedings of the International Conference on Machine Learning, 2023

FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU.

Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang

Proceedings of the International Conference on Machine Learning, 2023

2022

Petals: Collaborative Inference and Fine-tuning of Large Models.

Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers, Max Ryabinin, Younes Belkada, Artem Chumachenko, Pavel Samygin, Colin Raffel

CoRR, 2022

Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees.

Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander V. Gasnikov

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Secure Distributed Training at Scale.

Eduard Gorbunov, Alexander Borzunov, Michael Diskin, Max Ryabinin

Proceedings of the International Conference on Machine Learning, 2022

RuCoLA: Russian Corpus of Linguistic Acceptability.

Vladislav Mikhailov, Tatiana Shamardina, Max Ryabinin, Alena Pestova, Ivan Smurov, Ekaterina Artemova

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets.

Max Ryabinin, Andrey Malinin, Mark J. F. Gales

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

Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices.

Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko

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

Distributed Deep Learning In Open Collaborations.

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

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

Training Transformers Together.

Alexander Borzunov, Max Ryabinin, Tim Dettmers, Quentin Lhoest, Lucile Saulnier, Michael Diskin, Yacine Jernite, Thomas Wolf

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense Reasoning.

Alexey Tikhonov, Max Ryabinin

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts.

Max Ryabinin, Anton Gusev

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Embedding Words in Non-Vector Space with Unsupervised Graph Learning.

Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020