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2020 – today
- 2024
[c15]Anton Voronov, Lena Wolf, Max Ryabinin:
Mind Your Format: Towards Consistent Evaluation of In-Context Learning Improvements. ACL (Findings) 2024: 6287-6310- [i20]Anton Voronov, Lena Wolf, Max Ryabinin:
Mind Your Format: Towards Consistent Evaluation of In-Context Learning Improvements. CoRR abs/2401.06766 (2024) - [i19]Zhuoming Chen, Avner May, Ruslan Svirschevski, Yuhsun Huang, Max Ryabinin, Zhihao Jia, Beidi Chen:
Sequoia: Scalable, Robust, and Hardware-aware Speculative Decoding. CoRR abs/2402.12374 (2024) - [i18]Giwon Hong, Aryo Pradipta Gema
, Rohit Saxena, Xiaotang Du, Ping Nie, Yu Zhao, Laura Perez-Beltrachini, Max Ryabinin, Xuanli He, Clémentine Fourrier, Pasquale Minervini:
The Hallucinations Leaderboard - An Open Effort to Measure Hallucinations in Large Language Models. CoRR abs/2404.05904 (2024) - [i17]Ruslan Svirschevski, Avner May, Zhuoming Chen, Beidi Chen, Zhihao Jia, Max Ryabinin:
SpecExec: Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices. CoRR abs/2406.02532 (2024) - [i16]Jiayi Wang, Yao Lu, Maurice Weber, Max Ryabinin, Yihong Chen, Raphael Tang, Pontus Stenetorp:
Multilingual Pretraining Using a Large Corpus Machine-Translated from a Single Source Language. CoRR abs/2410.23956 (2024) - 2023
- [c14]Max Ryabinin, Tim Dettmers, Michael Diskin, Alexander Borzunov:
SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient. ICML 2023: 29416-29440 - [c13]Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang:
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. ICML 2023: 31094-31116 - [c12]Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin A. Raffel:
Distributed Inference and Fine-tuning of Large Language Models Over The Internet. NeurIPS 2023 - [c11]Anton Voronov, Mikhail Khoroshikh, Artem Babenko, Max Ryabinin:
Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics. NeurIPS 2023 - [i15]Max Ryabinin, Tim Dettmers, Michael Diskin, Alexander Borzunov:
SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient. CoRR abs/2301.11913 (2023) - [i14]Anton Voronov, Mikhail Khoroshikh, Artem Babenko, Max Ryabinin:
Is This Loss Informative? Speeding Up Textual Inversion with Deterministic Objective Evaluation. CoRR abs/2302.04841 (2023) - [i13]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:
High-throughput Generative Inference of Large Language Models with a Single GPU. CoRR abs/2303.06865 (2023) - [i12]Anton Baryshnikov, Max Ryabinin:
Hypernymy Understanding Evaluation of Text-to-Image Models via WordNet Hierarchy. CoRR abs/2310.09247 (2023) - [i11]Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin Raffel:
Distributed Inference and Fine-tuning of Large Language Models Over The Internet. CoRR abs/2312.08361 (2023) - 2022
- [c10]Vladislav Mikhailov, Tatiana Shamardina, Max Ryabinin, Alena Pestova, Ivan Smurov, Ekaterina Artemova:
RuCoLA: Russian Corpus of Linguistic Acceptability. EMNLP 2022: 5207-5227 - [c9]Eduard Gorbunov, Alexander Borzunov, Michael Diskin, Max Ryabinin:
Secure Distributed Training at Scale. ICML 2022: 7679-7739 - [c8]Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander V. Gasnikov:
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees. NeurIPS 2022 - [i10]Alexander Borzunov, Max Ryabinin, Tim Dettmers, Quentin Lhoest, Lucile Saulnier, Michael Diskin, Yacine Jernite, Thomas Wolf:
Training Transformers Together. CoRR abs/2207.03481 (2022) - [i9]Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers, Max Ryabinin, Younes Belkada, Artem Chumachenko, Pavel Samygin, Colin Raffel:
Petals: Collaborative Inference and Fine-tuning of Large Models. CoRR abs/2209.01188 (2022) - [i8]Vladislav Mikhailov, Tatiana Shamardina, Max Ryabinin, Alena Pestova, Ivan Smurov, Ekaterina Artemova:
RuCoLA: Russian Corpus of Linguistic Acceptability. CoRR abs/2210.12814 (2022) - 2021
- [c7]Alexey Tikhonov, Max Ryabinin:
It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense Reasoning. ACL/IJCNLP (Findings) 2021: 3534-3546 - [c6]Alexander Borzunov, Max Ryabinin, Tim Dettmers, Quentin Lhoest, Lucile Saulnier, Michael Diskin, Yacine Jernite, Thomas Wolf:
Training Transformers Together. NeurIPS (Competition and Demos) 2021: 335-342 - [c5]Max Ryabinin, Andrey Malinin, Mark J. F. Gales:
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets. NeurIPS 2021: 6023-6035 - [c4]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:
Distributed Deep Learning In Open Collaborations. NeurIPS 2021: 7879-7897 - [c3]Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko:
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices. NeurIPS 2021: 18195-18211 - [i7]Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko:
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices. CoRR abs/2103.03239 (2021) - [i6]Max Ryabinin, Andrey Malinin, Mark J. F. Gales:
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets. CoRR abs/2105.06987 (2021) - [i5]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:
Distributed Deep Learning in Open Collaborations. CoRR abs/2106.10207 (2021) - [i4]Eduard Gorbunov, Alexander Borzunov, Michael Diskin, Max Ryabinin:
Secure Distributed Training at Scale. CoRR abs/2106.11257 (2021) - [i3]Alexey Tikhonov, Max Ryabinin:
It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense Reasoning. CoRR abs/2106.12066 (2021) - [i2]Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander V. Gasnikov:
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees. CoRR abs/2110.03313 (2021) - 2020
- [c2]Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita:
Embedding Words in Non-Vector Space with Unsupervised Graph Learning. EMNLP (1) 2020: 7317-7331 - [c1]Max Ryabinin, Anton Gusev:
Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts. NeurIPS 2020 - [i1]Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita:
Embedding Words in Non-Vector Space with Unsupervised Graph Learning. CoRR abs/2010.02598 (2020)
Coauthor Index
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last updated on 2024-12-01 00:13 CET by the dblp team
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