Keerthiram Murugesan

93 papers A* 14A 1B 3Misc 2Journal 55Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AgentSCOPE: Evaluating Contextual Privacy Across Agentic Workflows. CoRR Ivoline C. Ngong, Keerthiram Murugesan, Swanand Kadhe, Justin D. Weisz, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy
2026	—	`conf`	Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use. EACL (Findings) Yiyang Li, Zehong Wang, Zhengqing Yuan, Zheyuan Zhang, Keerthiram Murugesan, Chuxu Zhang, Yanfang Ye
2026	J	`jnl`	LongDA: Benchmarking LLM Agents for Long-Document Data Analysis. CoRR Yiyang Li, Zheyuan Zhang, Tianyi Ma, Zehong Wang, Keerthiram Murugesan, Chuxu Zhang, Yanfang Ye
2026	—	`conf`	NG-Router: Graph-Supervised Multi-Agent Collaboration for Nutrition Question Answering. EACL (Volume 1: Long Papers) Kaiwen Shi, Zheyuan Zhang, Zhengqing Yuan, Keerthiram Murugesan, Vincent Galassi, Chuxu Zhang, Yanfang Ye
2026	J	`jnl`	The Unlearning Mirage: A Dynamic Framework for Evaluating LLM Unlearning. CoRR Raj Sanjay Shah, Jing Huang, Keerthiram Murugesan, Nathalie Baracaldo, Diyi Yang
2025	J	`jnl`	AgentRouter: A Knowledge-Graph-Guided LLM Router for Collaborative Multi-Agent Question Answering. CoRR Zheyuan Zhang, Kaiwen Shi, Zhengqing Yuan, Zehong Wang, Tianyi Ma, Keerthiram Murugesan, Vincent Galassi, Chuxu Zhang, Yanfang Ye
2025	—	`conf`	Are Large Language Models Effective in Clinical Trial Design? A Study on Baseline Feature Generation. NAACL (Findings) Nafis Neehal, Bowen Wang, Shayom Debopadhaya, Corey Curran, Keerthiram Murugesan, Soham Dan, Vibha Anand, Kristin P. Bennett
2025	J	`jnl`	AutoData: A Multi-Agent System for Open Web Data Collection. CoRR Tianyi Ma, Yiyue Qian, Zheyuan Zhang, Zehong Wang, Xiaoye Qian, Feifan Bai, Yifan Ding, Xuwei Luo, Shinan Zhang, Keerthiram Murugesan, Chuxu Zhang, Yanfang Ye
2025	J	`jnl`	Combinatorial Multi-armed Bandits: Arm Selection via Group Testing. Trans. Mach. Learn. Res. Arpan Mukherjee, Shashanka Ubaru, Keerthiram Murugesan, Karthikeyan Shanmugam, Ali Tajer
2025	J	`jnl`	Context Attribution with Multi-Armed Bandit Optimization. CoRR Deng Pan, Keerthiram Murugesan, Nuno Moniz, Nitesh V. Chawla
2025	J	`jnl`	Cross-Examiner: Evaluating Consistency of Large Language Model-Generated Explanations. CoRR Danielle Villa, Maria D. Chang, Keerthiram Murugesan, Rosario Uceda-Sosa, Karthikeyan Natesan Ramamurthy
2025	J	`jnl`	EfficientLLM: Efficiency in Large Language Models. CoRR Zhengqing Yuan, Weixiang Sun, Yixin Liu, Huichi Zhou, Rong Zhou, Yiyang Li, Zheyuan Zhang, Wei Song, Yue Huang, Haolong Jia, Keerthiram Murugesan, Yu Wang, Lifang He, Jianfeng Gao, Lichao Sun, Yanfang Ye
2025	J	`jnl`	Food4All: A Multi-Agent Framework for Real-time Free Food Discovery with Integrated Nutritional Metadata. CoRR Zhengqing Yuan, Yiyang Li, Weixiang Sun, Zheyuan Zhang, Kaiwen Shi, Keerthiram Murugesan, Yanfang Ye
2025	—	`conf`	Granite Guardian: Comprehensive LLM Safeguarding. NAACL (Industry Track) Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury, Tejaswini Pedapati, Pierre L. Dognin, Keerthiram Murugesan, Erik Miehling, Martín Santillán Cooper, Kieran Fraser, Giulio Zizzo, Muhammad Zaid Hameed, Mark Purcell, Michael Desmond, Qian Pan, Inge Vejsbjerg, Elizabeth M. Daly, Michael Hind, Werner Geyer, Ambrish Rawat, Kush R. Varshney, Prasanna Sattigeri
2025	J	`jnl`	Group Fair Federated Learning via Stochastic Kernel Regularization. Trans. Mach. Learn. Res. Huzaifa Arif, Pin-Yu Chen, Keerthiram Murugesan, Alex Gittens
2025	J	`jnl`	Highlight All the Phrases: Enhancing LLM Transparency through Visual Factuality Indicators. CoRR Hyo Jin Do, Rachel Ostrand, Werner Geyer, Keerthiram Murugesan, Dennis Wei, Justin D. Weisz
2025	J	`jnl`	Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use. CoRR Yiyang Li, Zehong Wang, Zhengqing Yuan, Zheyuan Zhang, Keerthiram Murugesan, Chuxu Zhang, Yanfang Ye
2025	J	`jnl`	Language Models Coupled with Metacognition Can Outperform Reasoning Models. CoRR Vedant Khandelwal, Francesca Rossi, Keerthiram Murugesan, Erik Miehling, Murray Campbell, Karthikeyan Natesan Ramamurthy, Lior Horesh
2025	—	`conf`	MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation. KDD (1) Zheyuan Zhang, Zehong Wang, Tianyi Ma, Varun Sameer Taneja, Sofia Nelson, Nhi Ha Lan Le, Keerthiram Murugesan, Mingxuan Ju, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2025	J	`jnl`	NG-Router: Graph-Supervised Multi-Agent Collaboration for Nutrition Question Answering. CoRR Kaiwen Shi, Zheyuan Zhang, Zhengqing Yuan, Keerthiram Murugesan, Vincent Galassi, Chuxu Zhang, Yanfang Ye
2025	—	`conf`	NGQA: A Nutritional Graph Question Answering Benchmark for Personalized Health-aware Nutritional Reasoning. ACL (1) Zheyuan Zhang, Yiyang Li, Nhi Ha Lan Le, Zehong Wang, Tianyi Ma, Vincent Galassi, Keerthiram Murugesan, Nuno Moniz, Werner Geyer, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2025	J	`jnl`	OjaKV: Context-Aware Online Low-Rank KV Cache Compression with Oja's Rule. CoRR Yuxuan Zhu, David H. Yang, Mohammad Mohammadi Amiri, Keerthiram Murugesan, Tejaswini Pedapati, Pin-Yu Chen
2025	B	`conf`	On the Effects of Fine-tuning Language Models for Text-Based Reinforcement Learning. COLING Maurício Gruppi, Soham Dan, Keerthiram Murugesan, Subhajit Chaudhury
2025	—	`conf`	PEEL the Layers and Find Yourself: Revisiting Inference-Time Data Leakage for Residual Neural Networks. SaTML Huzaifa Arif, Keerthiram Murugesan, Payel Das, Alex Gittens, Pin-Yu Chen
2025	J	`jnl`	PEEL the Layers and Find Yourself: Revisiting Inference-time Data Leakage for Residual Neural Networks. CoRR Huzaifa Arif, Keerthiram Murugesan, Payel Das, Alex Gittens, Pin-Yu Chen
2025	J	`jnl`	Patching LLM Like Software: A Lightweight Method for Improving Safety Policy in Large Language Models. CoRR Huzaifa Arif, Keerthiram Murugesan, Ching-Yun Ko, Pin-Yu Chen, Payel Das, Alex Gittens
2025	—	`conf`	Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents. ACL (Findings) Ivoline C. Ngong, Swanand Ravindra Kadhe, Hao Wang, Keerthiram Murugesan, Justin D. Weisz, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy
2025	J	`jnl`	Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents. CoRR Ivoline C. Ngong, Swanand Kadhe, Hao Wang, Keerthiram Murugesan, Justin D. Weisz, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy
2025	J	`jnl`	Sequential uncertainty quantification with contextual tensors for social targeting. Knowl. Inf. Syst. Tsuyoshi Idé, Keerthiram Murugesan, Djallel Bouneffouf, Naoki Abe
2025	J	`jnl`	Thinking Fast and Slow in Human and Machine Intelligence. Commun. ACM Francesco Fabiano, Marianna Bergamaschi Ganapini, Andrea Loreggia, Nicholas Mattei, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava, K. Brent Venable
2024	J	`jnl`	CTBench: A Comprehensive Benchmark for Evaluating Language Model Capabilities in Clinical Trial Design. CoRR Nafis Neehal, Bowen Wang, Shayom Debopadhaya, Soham Dan, Keerthiram Murugesan, Vibha Anand, Kristin P. Bennett
2024	J	`jnl`	Combinatorial Multi-armed Bandits: Arm Selection via Group Testing. CoRR Arpan Mukherjee, Shashanka Ubaru, Keerthiram Murugesan, Karthikeyan Shanmugam, Ali Tajer
2024	J	`jnl`	Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations. CoRR 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
2024	—	`conf`	EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning. EACL (1) Kinjal Basu, Keerthiram Murugesan, Subhajit Chaudhury, Murray Campbell, Kartik Talamadupula, Tim Klinger
2024	J	`jnl`	EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning. CoRR Kinjal Basu, Keerthiram Murugesan, Subhajit Chaudhury, Murray Campbell, Kartik Talamadupula, Tim Klinger
2024	B	`conf`	Examining Trustworthiness of LLM-as-a-Judge Systems in a Clinical Trial Design Benchmark. IEEE Big Data Corey Curran, Nafis Neehal, Keerthiram Murugesan, Kristin P. Bennett
2024	J	`jnl`	Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions. CoRR Hyo Jin Do, Rachel Ostrand, Justin D. Weisz, Casey Dugan, Prasanna Sattigeri, Dennis Wei, Keerthiram Murugesan, Werner Geyer
2024	J	`jnl`	Granite Guardian. CoRR Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury, Tejaswini Pedapati, Pierre L. Dognin, Keerthiram Murugesan, Erik Miehling, Martin Santillan Cooper, Kieran Fraser, Giulio Zizzo, Muhammad Zaid Hameed, Mark Purcell, Michael Desmond, Qian Pan, Zahra Ashktorab, Inge Vejsbjerg, Elizabeth M. Daly, Michael Hind, Werner Geyer, Ambrish Rawat, Kush R. Varshney, Prasanna Sattigeri
2024	—	`conf`	Language Guided Exploration for RL Agents in Text Environments. NAACL-HLT (Findings) Hitesh Golchha, Sahil Yerawar, Dhruvesh Patel, Soham Dan, Keerthiram Murugesan
2024	J	`jnl`	Language Guided Exploration for RL Agents in Text Environments. CoRR Hitesh Golchha, Sahil Yerawar, Dhruvesh Patel, Soham Dan, Keerthiram Murugesan
2024	Misc	`conf`	Leveraging Visual Handicaps for Text-Based Reinforcement Learning. ICASSP Subhajit Chaudhury, Keerthiram Murugesan, Thomas Carta, Kartik Talamadupula, Michiaki Tatsubori
2024	J	`jnl`	MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation. CoRR Zheyuan Zhang, Zehong Wang, Tianyi Ma, Varun Sameer Taneja, Sofia Nelson, Nhi Ha Lan Le, Keerthiram Murugesan, Mingxuan Ju, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2024	J	`jnl`	NGQA: A Nutritional Graph Question Answering Benchmark for Personalized Health-aware Nutritional Reasoning. CoRR Zheyuan Zhang, Yiyang Li, Nhi Ha Lan Le, Zehong Wang, Tianyi Ma, Vincent Galassi, Keerthiram Murugesan, Nuno Moniz, Werner Geyer, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2024	J	`jnl`	On the Effects of Fine-tuning Language Models for Text-Based Reinforcement Learning. CoRR Maurício Gruppi, Soham Dan, Keerthiram Murugesan, Subhajit Chaudhury
2024	A*	`conf`	On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS). ICAPS Vishal Pallagani, Bharath C. Muppasani, Kaushik Roy, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh, Amit P. Sheth
2024	J	`jnl`	On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS). CoRR Vishal Pallagani, Kaushik Roy, Bharath Muppasani, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh, Amit P. Sheth
2024	A*	`conf`	SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. ICML Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang
2024	J	`jnl`	SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. CoRR Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang
2024	—	`conf`	STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models. ACL (Findings) Shreyas Basavatia, Keerthiram Murugesan, Shivam Ratnakar
2024	J	`jnl`	STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models. CoRR Shreyas Basavatia, Keerthiram Murugesan, Shivam Ratnakar
2024	J	`jnl`	To Transfer or Not to Transfer: Suppressing Concepts from Source Representations. Trans. Mach. Learn. Res. Vijay Sadashivaiah, Keerthiram Murugesan, Ronny Luss, Pin-Yu Chen, Chris R. Sims, James A. Hendler, Amit Dhurandhar
2024	A*	`conf`	Towards Aligning Language Models with Textual Feedback. EMNLP Saüc Abadal Lloret, Shehzaad Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan
2024	J	`jnl`	Towards Aligning Language Models with Textual Feedback. CoRR Saüc Abadal Lloret, Shehzaad Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan
2024	Misc	`conf`	Variance Reduction Can Improve Trade-Off in Multi-Objective Learning. ICASSP Heshan Devaka Fernando, Lisha Chen, Songtao Lu, Pin-Yu Chen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Gaowen Liu, Meng Wang, Tianyi Chen
2023	J	`jnl`	Fast and Slow Planning. CoRR Francesco Fabiano, Vishal Pallagani, Marianna Bergamaschi Ganapini, Lior Horesh, Andrea Loreggia, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava
2023	—	`conf`	Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning. ACL (1) Subhajit Chaudhury, Sarathkrishna Swaminathan, Daiki Kimura, Prithviraj Sen, Keerthiram Murugesan, Rosario Uceda-Sosa, Michiaki Tatsubori, Achille Fokoue, Pavan Kapanipathi, Asim Munawar, Alexander Gray
2023	J	`jnl`	Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning. CoRR Subhajit Chaudhury, Sarathkrishna Swaminathan, Daiki Kimura, Prithviraj Sen, Keerthiram Murugesan, Rosario Uceda-Sosa, Michiaki Tatsubori, Achille Fokoue, Pavan Kapanipathi, Asim Munawar, Alexander Gray
2023	—	`conf`	MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types. ACL (Findings) 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
2023	J	`jnl`	MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types. CoRR 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
2023	A*	`conf`	Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach. ICLR Heshan Devaka Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Tianyi Chen
2023	A*	`conf`	On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. NeurIPS Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury
2023	J	`jnl`	On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. CoRR Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury
2023	A*	`conf`	Plansformer Tool: Demonstrating Generation of Symbolic Plans Using Transformers. IJCAI Vishal Pallagani, Bharath Muppasani, Biplav Srivastava, Francesca Rossi, Lior Horesh, Keerthiram Murugesan, Andrea Loreggia, Francesco Fabiano, Rony Joseph, Yathin Kethepalli
2023	A*	`conf`	Probabilistic Rule Induction from Event Sequences with Logical Summary Markov Models. IJCAI Debarun Bhattacharjya, Oktie Hassanzadeh, Ronny Luss, Keerthiram Murugesan
2023	J	`jnl`	Understanding the Capabilities of Large Language Models for Automated Planning. CoRR Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Biplav Srivastava, Lior Horesh, Francesco Fabiano, Andrea Loreggia
2023	—	`conf`	Value-based Fast and Slow AI Nudging. ETHAICS@IJCAI Marianna Bergamaschi Ganapini, Francesco Fabiano, Lior Horesh, Andrea Loreggia, Nicholas Mattei, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava, K. Brent Venable
2023	J	`jnl`	Value-based Fast and Slow AI Nudging. CoRR Marianna Bergamaschi Ganapini, Francesco Fabiano, Lior Horesh, Andrea Loreggia, Nicholas Mattei, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava, K. Brent Venable
2022	A*	`conf`	Auto-Transfer: Learning to Route Transferable Representations. ICLR Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar
2022	J	`jnl`	Auto-Transfer: Learning to Route Transferrable Representations. CoRR Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar
2022	A*	`conf`	Case-based reasoning for better generalization in textual reinforcement learning. ICLR Mattia Atzeni, Shehzaad Zuzar Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan
2022	A*	`conf`	Eye of the Beholder: Improved Relation Generalization for Text-Based Reinforcement Learning Agents. AAAI Keerthiram Murugesan, Subhajit Chaudhury, Kartik Talamadupula
2022	J	`jnl`	Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach. CoRR Heshan Devaka Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Tianyi Chen
2022	J	`jnl`	Plansformer: Generating Symbolic Plans using Transformers. CoRR Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Lior Horesh, Biplav Srivastava, Francesco Fabiano, Andrea Loreggia
2022	J	`jnl`	Targeted Advertising on Social Networks Using Online Variational Tensor Regression. CoRR Tsuyoshi Idé, Keerthiram Murugesan, Djallel Bouneffouf, Naoki Abe
2022	A*	`conf`	X-FACTOR: A Cross-metric Evaluation of Factual Correctness in Abstractive Summarization. EMNLP Subhajit Chaudhury, Sarathkrishna Swaminathan, R. Chulaka Gunasekara, Maxwell Crouse, Srinivas Ravishankar, Daiki Kimura, Keerthiram Murugesan, Ramón Fernandez Astudillo, Tahira Naseem, Pavan Kapanipathi, Alexander Gray
2021	J	`jnl`	Case-based Reasoning for Better Generalization in Text-Adventure Games. CoRR Mattia Atzeni, Shehzaad Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan
2021	—	`conf`	Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations. ACL/IJCNLP (2) Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell
2021	—	`conf`	Epistemic Planning in a Fast and Slow Setting. TFSOCTAI@AAAI Fall Symposium Francesco Fabiano, Marianna Bergamaschi Ganapini, Lior Horesh, Andrea Loreggia, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava
2021	J	`jnl`	Eye of the Beholder: Improved Relation Generalization for Text-based Reinforcement Learning Agents. CoRR Keerthiram Murugesan, Subhajit Chaudhury, Kartik Talamadupula
2021	A*	`conf`	Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines. AAAI Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell
2021	A*	`conf`	Thinking Fast and Slow in AI. AAAI Grady Booch, Francesco Fabiano, Lior Horesh, Kiran Kate, Jonathan Lenchner, Nick Linck, Andrea Loreggia, Keerthiram Murugesan, Nicholas Mattei, Francesca Rossi, Biplav Srivastava
2020	J	`jnl`	Enhancing Text-based Reinforcement Learning Agents with Commonsense Knowledge. CoRR Keerthiram Murugesan, Mattia Atzeni, Pushkar Shukla, Mrinmaya Sachan, Pavan Kapanipathi, Kartik Talamadupula
2020	J	`jnl`	Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines. CoRR Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell
2020	J	`jnl`	Thinking Fast and Slow in AI. CoRR Grady Booch, Francesco Fabiano, Lior Horesh, Kiran Kate, Jon Lenchner, Nick Linck, Andrea Loreggia, Keerthiram Murugesan, Nicholas Mattei, Francesca Rossi, Biplav Srivastava
2017	—	`conf`	Active Learning from Peers. NIPS Keerthiram Murugesan, Jaime G. Carbonell
2017	J	`jnl`	Co-Clustering for Multitask Learning. CoRR Keerthiram Murugesan, Jaime G. Carbonell, Yiming Yang
2017	A	`conf`	Multi-Task Multiple Kernel Relationship Learning. SDM Keerthiram Murugesan, Jaime G. Carbonell
2017	J	`jnl`	Multitask Matrix Completion for Learning Protein Interactions Across Diseases. J. Comput. Biol. Meghana Kshirsagar, Keerthiram Murugesan, Jaime G. Carbonell, Judith Klein-Seetharaman
2017	A*	`conf`	Self-Paced Multitask Learning with Shared Knowledge. IJCAI Keerthiram Murugesan, Jaime G. Carbonell
2017	J	`jnl`	Self-Paced Multitask Learning with Shared Knowledge. CoRR Keerthiram Murugesan, Jaime G. Carbonell
2016	—	`conf`	Adaptive Smoothed Online Multi-Task Learning. NIPS Keerthiram Murugesan, Hanxiao Liu, Jaime G. Carbonell, Yiming Yang
2016	J	`jnl`	Multi-Task Multiple Kernel Relationship Learning. CoRR Keerthiram Murugesan, Jaime G. Carbonell
2016	B	`conf`	Multitask Matrix Completion for Learning Protein Interactions Across Diseases. RECOMB Meghana Kshirsagar, Jaime G. Carbonell, Judith Klein-Seetharaman, Keerthiram Murugesan