Keerthiram Murugesan

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 55

Top Topics

Reinforcement Learning

Multiple Kernel

Provably Convergent

Top Venues

Publications

Kinjal Basu, Keerthiram Murugesan, Subhajit Chaudhury, Murray Campbell, Kartik Talamadupula, Tim Klinger
EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning. EACL (1) (2024)
Hyo Jin Do, Rachel Ostrand, Justin D. Weisz, Casey Dugan, Prasanna Sattigeri, Dennis Wei, Keerthiram Murugesan, Werner Geyer
Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions. CoRR (2024)
Subhajit Chaudhury, Keerthiram Murugesan, Thomas Carta, Kartik Talamadupula, Michiaki Tatsubori
Leveraging Visual Handicaps for Text-Based Reinforcement Learning. ICASSP (2024)
Hitesh Golchha, Sahil Yerawar, Dhruvesh Patel, Soham Dan, Keerthiram Murugesan
Language Guided Exploration for RL Agents in Text Environments. CoRR (2024)
Nafis Neehal, Bowen Wang, Shayom Debopadhaya, Soham Dan, Keerthiram Murugesan, Vibha Anand, Kristin P. Bennett
CTBench: A Comprehensive Benchmark for Evaluating Language Model Capabilities in Clinical Trial Design. CoRR (2024)
Vishal Pallagani, Kaushik Roy, Bharath Muppasani, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh, Amit P. Sheth
On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS). CoRR (2024)
Shreyas Basavatia, Keerthiram Murugesan, Shivam Ratnakar
STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models. ACL (Findings) (2024)
Maurício Gruppi, Soham Dan, Keerthiram Murugesan, Subhajit Chaudhury
On the Effects of Fine-tuning Language Models for Text-Based Reinforcement Learning. CoRR (2024)
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
Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations. CoRR (2024)
Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. CoRR (2024)
Kinjal Basu, Keerthiram Murugesan, Subhajit Chaudhury, Murray Campbell, Kartik Talamadupula, Tim Klinger
EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning. CoRR (2024)
Vishal Pallagani, Bharath C. Muppasani, Kaushik Roy, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh, Amit P. Sheth
On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS). ICAPS (2024)
Heshan Devaka Fernando, Lisha Chen, Songtao Lu, Pin-Yu Chen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Gaowen Liu, Meng Wang, Tianyi Chen
Variance Reduction Can Improve Trade-Off in Multi-Objective Learning. ICASSP (2024)
Saüc Abadal Lloret, Shehzaad Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan
Towards Aligning Language Models with Textual Feedback. CoRR (2024)
Vijay Sadashivaiah, Keerthiram Murugesan, Ronny Luss, Pin-Yu Chen, Chris R. Sims, James A. Hendler, Amit Dhurandhar
To Transfer or Not to Transfer: Suppressing Concepts from Source Representations. Trans. Mach. Learn. Res. 2024 (2024)
Shreyas Basavatia, Keerthiram Murugesan, Shivam Ratnakar
STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models. CoRR (2024)
Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava, Lior Horesh, Francesco Fabiano, Andrea Loreggia
Understanding the Capabilities of Large Language Models for Automated Planning. CoRR (2023)
Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. CoRR (2023)
Marianna Bergamaschi Ganapini, Francesco Fabiano, Lior Horesh, Andrea Loreggia, Nicholas Mattei, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava, Kristen Brent Venable
Value-based Fast and Slow AI Nudging. ETHAICS@IJCAI (2023)
Vishal Pallagani, Bharath Muppasani, Biplav Srivastava, Francesca Rossi, Lior Horesh, Keerthiram Murugesan, Andrea Loreggia, Francesco Fabiano, Rony Joseph, Yathin Kethepalli
Plansformer Tool: Demonstrating Generation of Symbolic Plans Using Transformers. IJCAI (2023)
Marianna Bergamaschi Ganapini, Francesco Fabiano, Lior Horesh, Andrea Loreggia, Nicholas Mattei, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava, Kristen Brent Venable
Value-based Fast and Slow AI Nudging. CoRR (2023)
Heshan Devaka Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Tianyi Chen
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach. ICLR (2023)
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
MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types. CoRR (2023)
Francesco Fabiano, Vishal Pallagani, Marianna Bergamaschi Ganapini, Lior Horesh, Andrea Loreggia, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava
Fast and Slow Planning. CoRR (2023)
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
MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types. ACL (Findings) (2023)
Subhajit Chaudhury, Sarathkrishna Swaminathan, Daiki Kimura, Prithviraj Sen, Keerthiram Murugesan, Rosario Uceda-Sosa, Michiaki Tatsubori, Achille Fokoue, Pavan Kapanipathi, Asim Munawar, Alexander Gray
Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning. ACL (1) (2023)
Subhajit Chaudhury, Sarathkrishna Swaminathan, Daiki Kimura, Prithviraj Sen, Keerthiram Murugesan, Rosario Uceda-Sosa, Michiaki Tatsubori, Achille Fokoue, Pavan Kapanipathi, Asim Munawar, Alexander Gray
Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning. CoRR (2023)
Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. NeurIPS (2023)
Debarun Bhattacharjya, Oktie Hassanzadeh, Ronny Luss, Keerthiram Murugesan
Probabilistic Rule Induction from Event Sequences with Logical Summary Markov Models. IJCAI (2023)
Keerthiram Murugesan, Subhajit Chaudhury, Kartik Talamadupula
Eye of the Beholder: Improved Relation Generalization for Text-Based Reinforcement Learning Agents. AAAI (2022)
Tsuyoshi Idé, Keerthiram Murugesan, Djallel Bouneffouf, Naoki Abe
Targeted Advertising on Social Networks Using Online Variational Tensor Regression. CoRR (2022)
Heshan Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Tianyi Chen
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach. CoRR (2022)
Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Lior Horesh, Biplav Srivastava, Francesco Fabiano, Andrea Loreggia
Plansformer: Generating Symbolic Plans using Transformers. CoRR (2022)
Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar
Auto-Transfer: Learning to Route Transferable Representations. ICLR (2022)
Mattia Atzeni, Shehzaad Zuzar Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan
Case-based reasoning for better generalization in textual reinforcement learning. ICLR (2022)
Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar
Auto-Transfer: Learning to Route Transferrable Representations. CoRR (2022)
Subhajit Chaudhury, Sarathkrishna Swaminathan, R. Chulaka Gunasekara, Maxwell Crouse, Srinivas Ravishankar, Daiki Kimura, Keerthiram Murugesan, Ramón Fernandez Astudillo, Tahira Naseem, Pavan Kapanipathi, Alexander Gray
X-FACTOR: A Cross-metric Evaluation of Factual Correctness in Abstractive Summarization. EMNLP (2022)
Francesco Fabiano, Marianna Bergamaschi Ganapini, Lior Horesh, Andrea Loreggia, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava
Epistemic Planning in a Fast and Slow Setting. TFSOCTAI@AAAI Fall Symposium (2021)
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell
Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations. ACL/IJCNLP (2) (2021)
Keerthiram Murugesan, Subhajit Chaudhury, Kartik Talamadupula
Eye of the Beholder: Improved Relation Generalization for Text-based Reinforcement Learning Agents. CoRR (2021)
Mattia Atzeni, Shehzaad Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan
Case-based Reasoning for Better Generalization in Text-Adventure Games. CoRR (2021)
Grady Booch, Francesco Fabiano, Lior Horesh, Kiran Kate, Jonathan Lenchner, Nick Linck, Andrea Loreggia, Keerthiram Murugesan, Nicholas Mattei, Francesca Rossi, Biplav Srivastava
Thinking Fast and Slow in AI. AAAI (2021)
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell
Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines. AAAI (2021)
Grady Booch, Francesco Fabiano, Lior Horesh, Kiran Kate, Jon Lenchner, Nick Linck, Andrea Loreggia, Keerthiram Murugesan, Nicholas Mattei, Francesca Rossi, Biplav Srivastava
Thinking Fast and Slow in AI. CoRR (2020)
Keerthiram Murugesan, Mattia Atzeni, Pushkar Shukla, Mrinmaya Sachan, Pavan Kapanipathi, Kartik Talamadupula
Enhancing Text-based Reinforcement Learning Agents with Commonsense Knowledge. CoRR (2020)
Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell
Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines. CoRR (2020)
Meghana Kshirsagar, Keerthiram Murugesan, Jaime G. Carbonell, Judith Klein-Seetharaman
Multitask Matrix Completion for Learning Protein Interactions Across Diseases. J. Comput. Biol. 24 (6) (2017)
Keerthiram Murugesan, Jaime G. Carbonell
Multi-Task Multiple Kernel Relationship Learning. SDM (2017)
Keerthiram Murugesan, Jaime G. Carbonell, Yiming Yang
Co-Clustering for Multitask Learning. CoRR (2017)
Keerthiram Murugesan, Jaime G. Carbonell
Self-Paced Multitask Learning with Shared Knowledge. IJCAI (2017)
Keerthiram Murugesan, Jaime G. Carbonell
Active Learning from Peers. NIPS (2017)
Keerthiram Murugesan, Jaime G. Carbonell
Self-Paced Multitask Learning with Shared Knowledge. CoRR (2017)
Keerthiram Murugesan, Jaime G. Carbonell
Multi-Task Multiple Kernel Relationship Learning. CoRR (2016)
Keerthiram Murugesan, Hanxiao Liu, Jaime G. Carbonell, Yiming Yang
Adaptive Smoothed Online Multi-Task Learning. NIPS (2016)
Meghana Kshirsagar, Jaime G. Carbonell, Judith Klein-Seetharaman, Keerthiram Murugesan
Multitask Matrix Completion for Learning Protein Interactions Across Diseases. RECOMB (2016)