---
title: "Ilya Sutskever — all works — Elamur Research"
description: "All 49 works of Ilya Sutskever in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/ilya-sutskever/works/"
---
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# Ilya Sutskever — all works

49 works · [← Ilya Sutskever](https://md.research.elamur.ai/free/en/authors/ilya-sutskever/)

1. **[Dropout: A Simple Way to Prevent Neural Networks from Overfitting ↗](https://jmlr.org/papers/v15/srivastava14a.html) JMLR 15(56):1929–1958 · no summary yet**Nitish Srivastava et al.*2014 · 34,422 citations*
2. [**Distributed Representations of Words and Phrases and their Compositionality arXiv:1310.4546**Tomas Mikolov, Ilya Sutskever, Kai Chen, et al.*2013 · 21,623 citations*](https://md.research.elamur.ai/free/en/papers/mikolov-2013-distributed-representations-words-phrases-their/)
3. [**Sequence to Sequence Learning with Neural Networks arXiv:1409.3215**Ilya Sutskever, Oriol Vinyals, Quoc V. Le*2014 · 18,409 citations*](https://md.research.elamur.ai/free/en/papers/sutskever-2014-sequence-sequence-learning-neural-networks/)
4. [**Learning Transferable Visual Models From Natural Language Supervision arXiv:2103.00020**Alec Radford, Jong Wook Kim, Chris Hallacy, et al.*2021 · 8,767 citations*](https://md.research.elamur.ai/free/en/papers/radford-2021-learning-transferable-visual-models-natural/)
5. **[Improving neural networks by preventing co-adaptation of feature detectors ↗](https://arxiv.org/abs/1207.0580) arXiv:1207.0580 · no summary yet**Geoffrey E. Hinton et al.*2012 · 6,645 citations*
6. [**Intriguing properties of neural networks arXiv:1312.6199**Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, et al.*2013 · 5,999 citations*](https://md.research.elamur.ai/free/en/papers/szegedy-2013-intriguing-properties-neural-networks/)
7. [**ImageNet Classification with Deep Convolutional Neural Networks NeurIPS 2012**Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton*2012 · 2,801 citations*](https://md.research.elamur.ai/free/en/papers/krizhevsky-2012-imagenet-classification-deep-convolutional/)
8. [**Robust Speech Recognition via Large-Scale Weak Supervision arXiv:2212.04356**Alec Radford, Jong Wook Kim, Tao Xu, et al.*2022 · 2,546 citations*](https://md.research.elamur.ai/free/en/papers/radford-2022-robust-speech-recognition-large-scale/)
9. [**Recurrent Neural Network Regularization arXiv:1409.2329**Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals*2014 · 2,412 citations*](https://md.research.elamur.ai/free/en/papers/zaremba-2014-recurrent-neural-network-regularization/)
10. **[Exploiting Similarities among Languages for Machine Translation ↗](https://arxiv.org/abs/1309.4168) arXiv:1309.4168 (2013) · no summary yet**Tomas Mikolov, Quoc V. Le, I. Sutskever*2013 · 1,838 citations*
11. [**Zero-Shot Text-to-Image Generation arXiv:2102.12092**Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, et al.*2021 · 1,528 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2021-zero-shot-text-image-generation/)
12. **[An Empirical Exploration of Recurrent Network Architectures ↗](https://openalex.org/W581956982) no summary yet**Rafał Józefowicz, Wojciech Zaremba, Ilya Sutskever*2015 · 1,415 citations*
13. [**Let's Verify Step by Step arXiv:2305.20050**Hunter Lightman, Vineet Kosaraju, Yura Burda, et al.*2023 · 1,412 citations*](https://md.research.elamur.ai/free/en/papers/lightman-2023-let-s-verify-step-step/)
14. **[InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets ↗](https://arxiv.org/abs/1606.03657) arXiv (Cornell University) · no summary yet**Chen, Xi et al.*2016 · 1,285 citations*
15. **[GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗](https://arxiv.org/abs/2112.10741) arXiv (Cornell University) · no summary yet**Alex Nichol et al.*2021 · 1,180 citations*
16. [**Generating Long Sequences with Sparse Transformers arXiv:1904.10509**Rewon Child, Scott Gray, Alec Radford, et al.*2019 · 967 citations*](https://md.research.elamur.ai/free/en/papers/child-2019-generating-long-sequences-sparse-transformers/)
17. **[Addressing the Rare Word Problem in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/luong-2015-addressing-rare-word-problem-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Thang Luong, Ilya Sutskever, Quoc Le, et al.*2015 · 832 citations*
18. **[Improved Variational Inference with Inverse Autoregressive Flow ↗](https://openalex.org/W2587284713) neural information processing systems · no summary yet**Durk Kingma et al.*2016 · 812 citations*
19. **[Grammar as a Foreign Language ↗](https://arxiv.org/abs/1412.7449) arXiv:1412.7449 · no summary yet**Oriol Vinyals et al.*2014 · 687 citations*
20. **[Generative Pretraining From Pixels ↗](https://openalex.org/W3034445277) International Conference on Machine Learning · no summary yet**Mark I-Cheng Chen et al.*2020 · 614 citations*
21. [**RL²: Fast Reinforcement Learning via Slow Reinforcement Learning arXiv:1611.02779**Yan Duan, John Schulman, Xi Chen, et al.*2016 · 524 citations*](https://md.research.elamur.ai/free/en/papers/duan-2016-rl-2-fast-reinforcement-learning/)
22. [**Learning to Generate Reviews and Discovering Sentiment arXiv:1704.01444**Alec Radford, Rafal Jozefowicz, Ilya Sutskever*2017 · 474 citations*](https://md.research.elamur.ai/free/en/papers/radford-2017-learning-generate-reviews-discovering-sentiment/)
23. **[Learning to Execute ↗](https://arxiv.org/abs/1410.4615) arXiv:1410.4615 · no summary yet**Wojciech Zaremba, Ilya Sutskever*2014 · 388 citations*
24. [**Multi-task Sequence to Sequence Learning arXiv:1511.06114**Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, et al.*2015 · 321 citations*](https://md.research.elamur.ai/free/en/papers/luong-2015-multi-task-sequence-sequence-learning/)
25. **[Neural GPUs Learn Algorithms ↗](https://arxiv.org/abs/1511.08228) arXiv:1511.08228 · no summary yet**Łukasz Kaiser, Ilya Sutskever*2015 · 305 citations*
26. **[Variational Lossy Autoencoder ↗](https://arxiv.org/abs/1611.02731) arXiv (Cornell University) · no summary yet**Xi Chen et al.*2016 · 285 citations*
27. **[Adding Gradient Noise Improves Learning for Very Deep Networks ↗](https://arxiv.org/abs/1511.06807) arXiv (Cornell University) · no summary yet**Arvind Neelakantan et al.*2015 · 274 citations*
28. **[Modelling Relational Data using Bayesian Clustered Tensor Factorization ↗](https://openalex.org/W2123228027) no summary yet**Ilya Sutskever, Ruslan Salakhutdinov, Joshua B. Tenenbaum*2009 · 255 citations*
29. [**Generative Language Modeling for Automated Theorem Proving arXiv:2009.03393**Stanislas Polu, Ilya Sutskever*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/)
30. **[Consistency Models ↗](https://arxiv.org/abs/2303.01469) arXiv (Cornell University) · no summary yet**Yang Song et al.*2023 · 235 citations*
31. **[One-Shot Imitation Learning ↗](https://openalex.org/W2963094133) neural information processing systems · no summary yet**Yan Duan et al.*2017 · 235 citations*
32. **[Improving Variational Inference with Inverse Autoregressive Flow ↗](https://arxiv.org/abs/1606.04934) arXiv (Cornell University) · no summary yet**Diederik P. Kingma et al.*2016 · 203 citations*
33. [**Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision arXiv:2312.09390**Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/burns-2023-weak-strong-generalization-eliciting-strong/)
34. **[Jukebox: A Generative Model for Music ↗](https://arxiv.org/abs/2005.00341) arXiv (Cornell University) · no summary yet**Prafulla Dhariwal et al.*2020 · 165 citations*
35. **[Scaling and evaluating sparse autoencoders ↗](https://arxiv.org/abs/2406.04093) arXiv:2406.04093 · no summary yet**Leo Gao et al.*2024 · 163 citations*
36. **[Neural Programmer: Inducing Latent Programs with Gradient Descent ↗](https://arxiv.org/abs/1511.04834) arXiv:1511.04834 · no summary yet**Arvind Neelakantan, Quoc V. Le, Ilya Sutskever*2015 · 142 citations*
37. **[Reinforcement Learning Neural Turing Machines - Revised ↗](https://arxiv.org/abs/1505.00521) arXiv:1505.00521 · no summary yet**Wojciech Zaremba, Ilya Sutskever*2015 · 139 citations*
38. [**Formal Mathematics Statement Curriculum Learning arXiv:2202.01344**Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.*2022 · 133 citations*](https://md.research.elamur.ai/free/en/papers/polu-2022-formal-mathematics-statement-curriculum-learning/)
39. **[GamePad: A Learning Environment for Theorem Proving ↗](https://arxiv.org/abs/1806.00608) arXiv:1806.00608 · no summary yet**Daniel Huang et al.*2018 · 94 citations*
40. **[Neural Random-Access Machines ↗](https://arxiv.org/abs/1511.06392) arXiv:1511.06392 · no summary yet**Karol Kurach, Marcin Andrychowicz, Ilya Sutskever*2015 · 50 citations*
41. **[An Online Sequence-to-Sequence Model Using Partial Conditioning ↗](https://arxiv.org/abs/1511.04868) arXiv (Cornell University) · no summary yet**Navdeep Jaitly et al.*2015 · 49 citations*
42. **[Distribution Augmentation for Generative Modeling ↗](https://openalex.org/W3114951884) International Conference on Machine Learning · no summary yet**Heewoo Jun et al.*2020 · 30 citations*
43. **[Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning ↗](https://openalex.org/W2161627023) no summary yet**Daniel Tarlow et al.*2013 · 30 citations*
44. **[Unsupervised Neural Machine Translation with Generative Language Models Only ↗](https://arxiv.org/abs/2110.05448) arXiv (Cornell University) · no summary yet**Jesse Michael Han et al.*2021 · 22 citations*
45. **[Towards Principled Unsupervised Learning ↗](https://arxiv.org/abs/1511.06440) arXiv (Cornell University) · no summary yet**Ilya Sutskever et al.*2015 · 21 citations*
46. **[Extensions and Limitations of the Neural GPU ↗](https://arxiv.org/abs/1611.00736) arXiv:1611.00736 · no summary yet**Eric Price, Wojciech Zaremba, Ilya Sutskever*2016 · 16 citations*
47. **[Conditional Augmentation for Generative Modeling ↗](https://openalex.org/W3035610106) International Conference on Machine Learning · no summary yet**Heewoo Jun et al.*2020*
48. **[tributed Representations of Words and Phrases and their Compositionality ” by ↗](https://openalex.org/W7097145127) no summary yet**Yoav Goldberg et al.*2014*
49. **[1 2 3 ↗](https://openalex.org/W7097211448) no summary yet**Kevin Swersky et al.*2013*