| Improving Language Understanding by Generative Pre-Training (GPT) A Radford, K Narasimhan, T Salimans, I Sutskever https://s3-us-west-2.amazonaws.com/openai-assets/research-covers/language …, 2018 | 7198* | 2018 |
| Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation TD Kulkarni, KR Narasimhan, A Saeedi, JB Tenenbaum Neural Information Processing Systems (NIPS), 2016 | 1226 | 2016 |
| Language understanding for text-based games using deep reinforcement learning K Narasimhan, T Kulkarni, R Barzilay Empirical Methods in Natural Language Processing (EMNLP), 2015 | 443 | 2015 |
| Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning K Narasimhan, A Yala, R Barzilay Empirical Methods in Natural Language Processing (EMNLP), 2016 | 178 | 2016 |
| React: Synergizing reasoning and acting in language models S Yao, J Zhao, D Yu, N Du, I Shafran, K Narasimhan, Y Cao arXiv preprint arXiv:2210.03629, 2022 | 169 | 2022 |
| A generalized algorithm for multi-objective reinforcement learning and policy adaptation R Yang, X Sun, K Narasimhan Advances in Neural Information Processing Systems (NeurIPS), 2019 | 168 | 2019 |
| Projection-Based Constrained Policy Optimization. TY Yang, J Rosca, K Narasimhan, PJ Ramadge International Conference on Learning Representations, 2020 | 155 | 2020 |
| Nonparametric Spherical Topic Modeling with Word Embeddings K Batmanghelich, A Saeedi, K Narasimhan, S Gershman Association for Computational Linguistics (ACL), 2016 | 116 | 2016 |
| Improving language understanding by generative pre-training R Alec, N Karthik, S Tim, S Ilya Technical report, OpenAI, 2018 | 101 | 2018 |
| Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge N Locascio, K Narasimhan, E DeLeon, N Kushman, R Barzilay Empirical Methods in Natural Language Processing (EMNLP), 2016 | 96 | 2016 |
| sk_p: a neural program corrector for MOOCs Y Pu, K Narasimhan, A Solar-Lezama, R Barzilay Companion Proceedings of the 2016 ACM SIGPLAN International Conference on …, 2016 | 88 | 2016 |
| Tree of thoughts: Deliberate problem solving with large language models S Yao, D Yu, J Zhao, I Shafran, TL Griffiths, Y Cao, K Narasimhan arXiv preprint arXiv:2305.10601, 2023 | 84 | 2023 |
| Machine Comprehension with Discourse Relations K Narasimhan, R Barzilay Association for Computational Linguistics (ACL), 2015 | 81 | 2015 |
| An Unsupervised Method for Uncovering Morphological Chains K Narasimhan, R Barzilay, T Jaakkola Transactions of the Association for Computational Linguistics (TACL), 2015 | 76 | 2015 |
| Grounding language for transfer in deep reinforcement learning K Narasimhan, R Barzilay, T Jaakkola Journal of Artificial Intelligence Research 63, 849-874, 2018 | 75 | 2018 |
| Representation learning for grounded spatial reasoning M Janner, K Narasimhan, R Barzilay Transactions of the Association for Computational Linguistics 6, 49-61, 2018 | 72 | 2018 |
| Keep CALM and Explore: Language Models for Action Generation in Text-based Games S Yao, R Rao, M Hausknecht, K Narasimhan Empirical Methods in Natural Language Processing (EMNLP), 2020 | 69 | 2020 |
| Reflexion: an autonomous agent with dynamic memory and self-reflection N Shinn, F Cassano, B Labash, A Gopinath, K Narasimhan, S Yao arXiv preprint arXiv:2303.11366, 2023 | 64 | 2023 |
| Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation Z Deng, K Narasimhan, O Russakovsky Advances in Neural Information Processing Systems 33, 2020 | 59 | 2020 |
| Universal adversarial attacks with natural triggers for text classification L Song, X Yu, HT Peng, K Narasimhan Annual Conference of the North American Chapter of the Association for …, 2020 | 56 | 2020 |
Tim SalimansGoogle Brain AmsterdamVerified email at google.com
