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Karthik Narasimhan
Karthik Narasimhan
Associate Professor, Princeton University
Dirección de correo verificada de princeton.edu - Página principal
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Citado por
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Año
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
12651*2018
React: Synergizing reasoning and acting in language models
S Yao, J Zhao, D Yu, N Du, I Shafran, K Narasimhan, Y Cao
International Conference on Learning Representations (ICLR), 2023
18052023
Tree of thoughts: Deliberate problem solving with large language models
S Yao, D Yu, J Zhao, I Shafran, TL Griffiths, Y Cao, K Narasimhan
Neural Information Processing Systems (NeurIPS), 2023
17782023
Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation
TD Kulkarni, KR Narasimhan, A Saeedi, JB Tenenbaum
Neural Information Processing Systems (NIPS), 2016
14642016
Reflexion: Language agents with verbal reinforcement learning
N Shinn, F Cassano, A Gopinath, K Narasimhan, S Yao
Advances in Neural Information Processing Systems 36, 2024
1190*2024
Language understanding for text-based games using deep reinforcement learning
K Narasimhan, T Kulkarni, R Barzilay
Empirical Methods in Natural Language Processing (EMNLP), 2015
4872015
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
3042019
Webshop: Towards scalable real-world web interaction with grounded language agents
S Yao, H Chen, J Yang, K Narasimhan
Advances in Neural Information Processing Systems (NeurIPS), 2022
2992022
Toxicity in chatgpt: Analyzing persona-assigned language models
A Deshpande, V Murahari, T Rajpurohit, A Kalyan, K Narasimhan
Findings of EMNLP, 2023
2982023
Projection-Based Constrained Policy Optimization.
TY Yang, J Rosca, K Narasimhan, PJ Ramadge
International Conference on Learning Representations, 2020
2832020
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
CE Jimenez, J Yang, A Wettig, S Yao, K Pei, O Press, K Narasimhan
International Conference on Learning Representations (ICLR), 2024
2202024
Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning
K Narasimhan, A Yala, R Barzilay
Empirical Methods in Natural Language Processing (EMNLP), 2016
1942016
Cognitive architectures for language agents
TR Sumers, S Yao, K Narasimhan, TL Griffiths
arXiv preprint arXiv:2309.02427, 2023
1682023
Nonparametric Spherical Topic Modeling with Word Embeddings
K Batmanghelich, A Saeedi, K Narasimhan, S Gershman
Association for Computational Linguistics (ACL), 2016
1302016
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
1282020
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
1122016
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
1102016
Grounding language for transfer in deep reinforcement learning
K Narasimhan, R Barzilay, T Jaakkola
Journal of Artificial Intelligence Research 63, 849-874, 2018
972018
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
882020
Self-Attention Networks Can Process Bounded Hierarchical Languages
S Yao, B Peng, C Papadimitriou, K Narasimhan
ACL, 2021
872021
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Artículos 1–20