Keerthiram Murugesan

According to our database, Keerthiram Murugesan authored at least 42 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

To Transfer or Not to Transfer: Suppressing Concepts from Source Representations.

Vijay Sadashivaiah, Keerthiram Murugesan, Ronny Luss, Pin-Yu Chen, Chris R. Sims, James A. Hendler, Amit Dhurandhar

Trans. Mach. Learn. Res., 2024

Towards Aligning Language Models with Textual Feedback.

Saüc Abadal Lloret, Shehzaad Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan

CoRR, 2024

CTBench: A Comprehensive Benchmark for Evaluating Language Model Capabilities in Clinical Trial Design.

Nafis Neehal, Bowen Wang, Shayom Debopadhaya, Soham Dan, Keerthiram Murugesan, Vibha Anand, Kristin P. Bennett

CoRR, 2024

Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions.

Hyo Jin Do, Rachel Ostrand, Justin D. Weisz, Casey Dugan, Prasanna Sattigeri, Dennis Wei, Keerthiram Murugesan, Werner Geyer

CoRR, 2024

On the Effects of Fine-tuning Language Models for Text-Based Reinforcement Learning.

Maurício Gruppi, Soham Dan, Keerthiram Murugesan, Subhajit Chaudhury

CoRR, 2024

Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations.

Swapnaja Achintalwar, Adriana Alvarado Garcia, Ateret Anaby-Tavor, Ioana Baldini, Sara E. Berger, Bishwaranjan Bhattacharjee, Djallel Bouneffouf, Subhajit Chaudhury, Pin-Yu Chen, Lamogha Chiazor, Elizabeth M. Daly, Rogério Abreu de Paula, Pierre L. Dognin, Eitan Farchi, Soumya Ghosh, Michael Hind, Raya Horesh, George Kour, Ja Young Lee, Erik Miehling, Keerthiram Murugesan, Manish Nagireddy, Inkit Padhi, David Piorkowski, Ambrish Rawat, Orna Raz, Prasanna Sattigeri, Hendrik Strobelt, Sarathkrishna Swaminathan, Christoph Tillmann, Aashka Trivedi, Kush R. Varshney, Dennis Wei, Shalisha Witherspoon, Marcel Zalmanovici

CoRR, 2024

Language Guided Exploration for RL Agents in Text Environments.

Hitesh Golchha, Sahil Yerawar, Dhruvesh Patel, Soham Dan, Keerthiram Murugesan

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning.

Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Variance Reduction Can Improve Trade-Off in Multi-Objective Learning.

Heshan Devaka Fernando, Lisha Chen, Songtao Lu, Pin-Yu Chen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Gaowen Liu, Meng Wang, Tianyi Chen

Proceedings of the IEEE International Conference on Acoustics, 2024

Leveraging Visual Handicaps for Text-Based Reinforcement Learning.

Subhajit Chaudhury, Keerthiram Murugesan, Thomas Carta, Kartik Talamadupula, Michiaki Tatsubori

Proceedings of the IEEE International Conference on Acoustics, 2024

On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS).

Vishal Pallagani, Bharath C. Muppasani, Kaushik Roy, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh, Amit P. Sheth

Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning.

Kinjal Basu, Keerthiram Murugesan, Subhajit Chaudhury, Murray Campbell, Kartik Talamadupula, Tim Klinger

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models.

Shreyas Basavatia, Keerthiram Murugesan, Shivam Ratnakar

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Understanding the Capabilities of Large Language Models for Automated Planning.

Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava, Lior Horesh, Francesco Fabiano, Andrea Loreggia

CoRR, 2023

Fast and Slow Planning.

Francesco Fabiano, Vishal Pallagani, Marianna Bergamaschi Ganapini, Lior Horesh, Andrea Loreggia, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava

CoRR, 2023

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration.

Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Plansformer Tool: Demonstrating Generation of Symbolic Plans Using Transformers.

Vishal Pallagani, Bharath Muppasani, Biplav Srivastava, Francesca Rossi, Lior Horesh, Keerthiram Murugesan, Andrea Loreggia, Francesco Fabiano, Rony Joseph, Yathin Kethepalli

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Probabilistic Rule Induction from Event Sequences with Logical Summary Markov Models.

Debarun Bhattacharjya, Oktie Hassanzadeh, Ronny Luss, Keerthiram Murugesan

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach.

Heshan Devaka Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Tianyi Chen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Value-based Fast and Slow AI Nudging.

Marianna Bergamaschi Ganapini, Francesco Fabiano, Lior Horesh, Andrea Loreggia, Nicholas Mattei, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava, Kristen Brent Venable

Proceedings of the Workshop on Ethics and Trust in Human-AI Collaboration: Socio-Technical Approaches (ETHAICS 2023) co-located with 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023) Macao, 2023

MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types.

Keerthiram Murugesan, Sarathkrishna Swaminathan, Soham Dan, Subhajit Chaudhury, R. Chulaka Gunasekara, Maxwell Crouse, Diwakar Mahajan, Ibrahim Abdelaziz, Achille Fokoue, Pavan Kapanipathi, Salim Roukos, Alexander Gray

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning.

Subhajit Chaudhury, Sarathkrishna Swaminathan, Daiki Kimura, Prithviraj Sen, Keerthiram Murugesan, Rosario Uceda-Sosa, Michiaki Tatsubori, Achille Fokoue, Pavan Kapanipathi, Asim Munawar, Alexander Gray

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Plansformer: Generating Symbolic Plans using Transformers.

Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Lior Horesh, Biplav Srivastava, Francesco Fabiano, Andrea Loreggia

CoRR, 2022

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach.

Heshan Devaka Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Tianyi Chen

CoRR, 2022

Targeted Advertising on Social Networks Using Online Variational Tensor Regression.

Tsuyoshi Idé, Keerthiram Murugesan, Djallel Bouneffouf, Naoki Abe

CoRR, 2022

Auto-Transfer: Learning to Route Transferrable Representations.

Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar

CoRR, 2022

Auto-Transfer: Learning to Route Transferable Representations.

Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar

Proceedings of the Tenth International Conference on Learning Representations, 2022

Case-based reasoning for better generalization in textual reinforcement learning.

Mattia Atzeni, Shehzaad Zuzar Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan

Proceedings of the Tenth International Conference on Learning Representations, 2022

X-FACTOR: A Cross-metric Evaluation of Factual Correctness in Abstractive Summarization.

Subhajit Chaudhury, Sarathkrishna Swaminathan, R. Chulaka Gunasekara, Maxwell Crouse, Srinivas Ravishankar, Daiki Kimura, Keerthiram Murugesan, Ramón Fernandez Astudillo, Tahira Naseem, Pavan Kapanipathi, Alexander Gray

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Eye of the Beholder: Improved Relation Generalization for Text-Based Reinforcement Learning Agents.

Keerthiram Murugesan, Subhajit Chaudhury, Kartik Talamadupula

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Case-based Reasoning for Better Generalization in Text-Adventure Games.

Mattia Atzeni, Shehzaad Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan

CoRR, 2021

Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations.

Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Epistemic Planning in a Fast and Slow Setting.

Francesco Fabiano, Marianna Bergamaschi Ganapini, Lior Horesh, Andrea Loreggia, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava

Proceedings of the Thinking Fast and Slow and Other Cognitive Theories in AI, 2021

Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines.

Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Thinking Fast and Slow in AI.

Grady Booch, Francesco Fabiano, Lior Horesh, Kiran Kate, Jonathan Lenchner, Nick Linck, Andrea Loreggia, Keerthiram Murugesan, Nicholas Mattei, Francesca Rossi, Biplav Srivastava

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Enhancing Text-based Reinforcement Learning Agents with Commonsense Knowledge.

Keerthiram Murugesan, Mattia Atzeni, Pushkar Shukla, Mrinmaya Sachan, Pavan Kapanipathi, Kartik Talamadupula

CoRR, 2020

2017

Multitask Matrix Completion for Learning Protein Interactions Across Diseases.

Meghana Kshirsagar, Keerthiram Murugesan, Jaime G. Carbonell, Judith Klein-Seetharaman

J. Comput. Biol., 2017

Co-Clustering for Multitask Learning.

Keerthiram Murugesan, Jaime G. Carbonell, Yiming Yang

CoRR, 2017

Multi-Task Multiple Kernel Relationship Learning.

Keerthiram Murugesan, Jaime G. Carbonell

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Active Learning from Peers.

Keerthiram Murugesan, Jaime G. Carbonell

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Self-Paced Multitask Learning with Shared Knowledge.

Keerthiram Murugesan, Jaime G. Carbonell

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Adaptive Smoothed Online Multi-Task Learning.

Keerthiram Murugesan, Hanxiao Liu, Jaime G. Carbonell, Yiming Yang

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016