preprint

  1. Safe Reinforcement Learning with Natural Language Constraints. Tsung-Yen Yang, Michael Hu, Yinlam Chow, Peter J. Ramadge, Karthik Narasimhan [abstract] [paper]
  2. Connecting Context-specific Adaptation in Humans to Meta-learning. Rachit Dubey, Erin Grant, Michael Luo, Karthik Narasimhan, Thomas Griffiths [abstract] [paper]

2021

  1. Grounding Language to Entities and Dynamics for Generalization in Reinforcement Learning. Austin W. Hanjie, Victor Zhong, Karthik Narasimhan International Conference on Machine Learning (ICML)  2021 [abstract] [paper]
  2. Accelerating Safe Reinforcement Learning with Constraint-mismatched Policies. Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, Peter J. Ramadge International Conference on Machine Learning (ICML)  2021 [abstract] [paper]
  3. Improving Dialog Systems for Negotiation with Personality Modeling. Runzhe Yang*, Jingxiao Chen*, Karthik Narasimhan Association for Computational Linguistics (ACL)  2021 [abstract] [paper]
  4. Self-Attention Networks Can Process Bounded Hierarchical Languages. Shunyu Yao, Binghui Peng, Christos Papadimitriou, Karthik Narasimhan Association for Computational Linguistics (ACL)  2021 [abstract] [paper]
  5. Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents. Shunyu Yao, Karthik Narasimhan, Matthew Hausknecht Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)  2021 [abstract] [paper]
  6. Universal Adversarial Attacks with Natural Triggers for Text Classification. Liwei Song*, Xinwei Yu*, Hsuan-Tung Peng*, Karthik Narasimhan Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)  2021 [abstract] [paper]
  7. Learning Rewards from Linguistic Feedback. Theodore R. Sumers, Mark K. Ho, Robert D. Hawkins, Karthik Narasimhan, Thomas L. Griffiths Thirty-Fifth AAAI Conference on Artificial Intelligence  2021 [abstract] [paper]
  8. m-Stage Epsilon-Greedy Exploration for Reinforcement Learning. Rohan Rao, Karthik Narasimhan AAAI-21 Workshop on Reinforcement Learning in Games  2021 [abstract] [paper]

2020

  1. Keep CALM and Explore: Language Models for Action Generation in Text-based Games. Shunyu Yao, Rohan Rao, Matthew Hausknecht, Karthik Narasimhan Empirical Methods in Natural Language Processing (EMNLP)  2020 [abstract] [paper]
  2. Guiding Attention for Self-Supervised Learning with Transformers. Ameet Deshpande, Karthik Narasimhan Findings of Empirical Methods in Natural Language Processing (EMNLP)  2020 [abstract] [paper]
  3. Robust and Interpretable Grounding of Spatial References with Relation Networks. Tsung-Yen Yang, Andrew S. Lan, Karthik Narasimhan Findings of Empirical Methods in Natural Language Processing (EMNLP)  2020 [abstract] [paper]
  4. Multimodal Graph Networks for Compositional Generalization in Visual Question Answering. Raeid Saqur, Karthik Narasimhan Neural Information Processing Systems (NeurIPS)  2020 [abstract] [paper]
  5. Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation. Zhiwei Deng, Karthik Narasimhan, Olga Russakovsky Neural Information Processing Systems (NeurIPS)  2020 [abstract] [paper]
  6. Towards Unique and Informative Captioning of Images. Zeyu Wang, Berthy Feng, Karthik Narasimhan, Olga Russakovsky European Conference on Computer Vision (ECCV)  2020 [abstract] [paper]
  7. Calibration, Entropy Rates, and Memory in Language Models. Mark Braverman, Xinyi Chen, Sham Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang International Conference on Machine Learning (ICML)  2020 [abstract] [paper]
  8. Projection Based Constrained Policy Optimization. Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, Peter J. Ramadge International Conference on Learning Representations (ICLR)  2020 [abstract] [paper]
  9. Take the scenic route: improving generalization in vision-and-language navigation. Felix Yu, Zhiwei Deng, Karthik Narasimhan, Olga Russakovsky CVPR Visual Learning with Limited Labels Workshop  2020 [abstract] [paper]

2019

  1. A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation. Runzhe Yang, Xingyuan Sun, Karthik Narasimhan Neural Information Processing Systems (NeurIPS)  2019 [abstract] [paper]
  2. Task-Agnostic Dynamics Priors for Deep Reinforcement Learning. Yilun Du, Karthik Narasimhan International Conference on Machine Learning (ICML)  2019 [abstract] [paper] [code]
  3. A System-Wide Debugging Assistant Powered by Natural Language Processing. Pradeep Dogga, Karthik Narasimhan, Anirudh Sivaraman, Ravi Netravali Proceedings of the ACM Symposium on Cloud Computing  2019

2018

  1. Deep Transfer in Reinforcement Learning by Language Grounding. Karthik Narasimhan, Regina Barzilay, Tommi Jaakkola Journal of Artificial Intelligence Research (JAIR)  2018 [abstract] [paper] [code]
  2. Improving language understanding by generative pre-training. Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever Technical Report  2018 [abstract] [paper]

2017

  1. Grounding Natural Language with Autonomous Interaction. Karthik Narasimhan PhD Thesis  2017 [abstract] [paper]
  2. Representation Learning for Grounded Spatial Reasoning. Michael Janner, Karthik Narasimhan, Regina Barzilay Transactions of the Association for Computational Linguistics (TACL)  2017 [abstract] [paper] [code]
  3. Unsupervised Learning of Morphological Forests. Jiaming Luo, Karthik Narasimhan, Regina Barzilay Transactions of the Association for Computational Linguistics (TACL)  2017 [abstract] [paper] [code]
  4. Constructing sub-word units for Spoken Term Detection. Charl Heerden, Damianos Karakos, Karthik Narasimhan, Marelie Davel, Richard Schwartz IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  2017 [abstract] [paper]

2016

  1. Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning. Karthik Narasimhan, Adam Yala, Regina Barzilay Empirical Methods in Natural Language Processing (EMNLP)  2016 (Best paper award) [abstract] [paper] [slides] [code] [media: MIT news, Digital Trends, TechRadar, Economic Times]
  2. Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation. Tejas D Kulkarni*, Karthik R Narasimhan*, Ardavan Saeedi, Joshua B Tenenbaum Neural Information Processing Systems (NIPS)  2016 [abstract] [paper] [code]
  3. Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge. Nicholas Locascio, Karthik Narasimhan, Eduardo DeLeon, Nate Kushman, Regina Barzilay Empirical Methods in Natural Language Processing (EMNLP)  2016 [abstract] [paper] [code] [media: Hacker news]
  4. Nonparametric Spherical Topic Modeling with Word Embeddings. Kayhan Batmanghelich, Ardavan Saeedi, Karthik Narasimhan, Sam Gershman Association for Computational Linguistics (ACL)  2016 [abstract] [paper] [code]

2015

  1. Language understanding for text-based games using deep reinforcement learning. Karthik Narasimhan*, Tejas Kulkarni*, Regina Barzilay Empirical Methods in Natural Language Processing (EMNLP)  2015 (Best paper honorable mention) [abstract] [paper] [supp] [slides] [code] [media: MIT news, Hacker news, Evennia blog]
  2. An Unsupervised Method for Uncovering Morphological Chains. Karthik Narasimhan, Regina Barzilay, Tommi Jaakkola Transactions of the Association for Computational Linguistics (TACL)  2015 [abstract] [paper] [slides] [code] [resources]
  3. Machine Comprehension with Discourse Relations. Karthik Narasimhan, Regina Barzilay Association for Computational Linguistics (ACL)  2015 [abstract] [paper] [slides] [resources]
  4. JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes. Jonathan H Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash K Mansinghka International Conference on Machine Learning (ICML)  2015 [abstract] [paper]

2014

  1. Morphological Segmentation for Keyword Spotting. Karthik Narasimhan, Damianos Karakos, Richard Schwartz, Stavros Tsakalidis, Regina Barzilay Empirical Methods in Natural Language Processing (EMNLP)  2014 [abstract] [paper] [poster]

2012

  1. Modeling human bounded rationality to improve defender strategies in network security games. Rong Yang, Fei Fang, Albert Xin Jiang, Karthik Rajagopal, Milind Tambe, Rajiv Maheswaran HAIDM workshop at AAMAS  2012 [abstract] [paper]