Jayakumar Subramanian

35 papers A* 3A 4C 2Misc 1Journal 21Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Rethinking Failure Attribution in Multi-Agent Systems: A Multi-Perspective Benchmark and Evaluation. CoRR Yeonjun In, Mehrab Tanjim, Jayakumar Subramanian, Sungchul Kim, Uttaran Bhattacharya, Wonjoong Kim, Sangwu Park, Somdeb Sarkhel, Chanyoung Park
2025	C	`conf`	AsyncVoice Agent: Real-Time Explanation for LLM Planning and Reasoning. ASRU Yueqian Lin, Zhengmian Hu, Jayakumar Subramanian, Qinsi Wang, Nikos Vlassis, Hai Li, Yiran Chen
2025	J	`jnl`	AsyncVoice Agent: Real-Time Explanation for LLM Planning and Reasoning. CoRR Yueqian Lin, Zhengmian Hu, Jayakumar Subramanian, Qinsi Wang, Nikos Vlassis, Hai Helen Li, Yiran Chen
2025	J	`jnl`	Learning to Clarify by Reinforcement Learning Through Reward-Weighted Fine-Tuning. CoRR Subhojyoti Mukherjee, Viet Dac Lai, Raghavendra Addanki, Ryan A. Rossi, Seunghyun Yoon, Trung Bui, Anup B. Rao, Jayakumar Subramanian, Branislav Kveton
2025	J	`jnl`	Lizard: An Efficient Linearization Framework for Large Language Models. CoRR Chien Van Nguyen, Ruiyi Zhang, Hanieh Deilamsalehy, Puneet Mathur, Viet Dac Lai, Haoliang Wang, Jayakumar Subramanian, Ryan A. Rossi, Trung Bui, Nikos Vlassis, Franck Dernoncourt, Thien Huu Nguyen
2025	A*	`conf`	Measuring And Improving Engagement of Text-to-Image Generation Models. ICLR Varun Khurana, Yaman Kumar Singla, Jayakumar Subramanian, Changyou Chen, Rajiv Ratn Shah, Zhiqiang Xu, Balaji Krishnamurthy
2025	J	`jnl`	Voice Evaluation of Reasoning Ability: Diagnosing the Modality-Induced Performance Gap. CoRR Yueqian Lin, Zhengmian Hu, Qinsi Wang, Yudong Liu, Hengfan Zhang, Jayakumar Subramanian, Nikos Vlassis, Hai Helen Li, Yiran Chen
2024	A	`conf`	flame: A Framework for Learning in Agent-based ModEls. AAMAS Ayush Chopra, Jayakumar Subramanian, Balaji Krishnamurthy, Ramesh Raskar
2023	J	`jnl`	Behavior Optimized Image Generation. CoRR Varun Khurana, Yaman Kumar Singla, Jayakumar Subramanian, Rajiv Ratn Shah, Changyou Chen, Zhiqiang Xu, Balaji Krishnamurthy
2023	J	`jnl`	Counterfactual Explanation Policies in RL. CoRR Shripad Vilasrao Deshmukh, Srivatsan R, Supriti Vijay, Jayakumar Subramanian, Chirag Agarwal
2023	A	`conf`	Differentiable Agent-based Epidemiology. AAMAS Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Arnau Quera-Bofarull, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar
2023	A*	`conf`	Explaining RL Decisions with Trajectories. ICLR Shripad Vilasrao Deshmukh, Arpan Dasgupta, Balaji Krishnamurthy, Nan Jiang, Chirag Agarwal, Georgios Theocharous, Jayakumar Subramanian
2023	J	`jnl`	Explaining RL Decisions with Trajectories. CoRR Shripad Vilasrao Deshmukh, Arpan Dasgupta, Balaji Krishnamurthy, Nan Jiang, Chirag Agarwal, Georgios Theocharous, Jayakumar Subramanian
2023	J	`jnl`	Mean-field games among teams. CoRR Jayakumar Subramanian, Akshat Kumar, Aditya Mahajan
2023	J	`jnl`	Robustness and Sample Complexity of Model-Based MARL for General-Sum Markov Games. Dyn. Games Appl. Jayakumar Subramanian, Amit Sinha, Aditya Mahajan
2023	J	`jnl`	SARC: Soft Actor Retrospective Critic. CoRR Sukriti Verma, Ayush Chopra, Jayakumar Subramanian, Mausoom Sarkar, Nikaash Puri, Piyush Gupta, Balaji Krishnamurthy
2022	J	`jnl`	Approximate Information State for Approximate Planning and Reinforcement Learning in Partially Observed Systems. J. Mach. Learn. Res. Jayakumar Subramanian, Amit Sinha, Raihan Seraj, Aditya Mahajan
2022	J	`jnl`	Differentiable Agent-based Epidemiology. CoRR Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar
2022	A	`conf`	Status-quo Policy Gradient in Multi-Agent Reinforcement Learning. AAMAS Pinkesh Badjatiya, Mausoom Sarkar, Nikaash Puri, Jayakumar Subramanian, Abhishek Sinha, Siddharth Singh, Balaji Krishnamurthy
2021	Misc	`conf`	DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks - a Case Study For Covid-19 Spread and Interventions. WSC Ayush Chopra, Ramesh Raskar, Jayakumar Subramanian, Balaji Krishnamurthy, Esma Senturk Gel, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley
2021	J	`jnl`	DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks. CoRR Ayush Chopra, Esma Senturk Gel, Jayakumar Subramanian, Balaji Krishnamurthy, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley, Ramesh Raskar
2021	A*	`conf`	Medical Dead-ends and Learning to Identify High-Risk States and Treatments. NeurIPS Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi
2021	J	`jnl`	Medical Dead-ends and Learning to Identify High-risk States and Treatments. CoRR Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi
2021	J	`jnl`	Robustness and sample complexity of model-based MARL for general-sum Markov games. CoRR Jayakumar Subramanian, Amit Sinha, Aditya Mahajan
2021	J	`jnl`	Status-quo policy gradient in Multi-Agent Reinforcement Learning. CoRR Pinkesh Badjatiya, Mausoom Sarkar, Nikaash Puri, Jayakumar Subramanian, Abhishek Sinha, Siddharth Singh, Balaji Krishnamurthy
2020	—	`conf`	An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. ML4H@NeurIPS Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi
2020	J	`jnl`	An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. CoRR Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi
2020	J	`jnl`	Approximate information state for approximate planning and reinforcement learning in partially observed systems. CoRR Jayakumar Subramanian, Amit Sinha, Raihan Seraj, Aditya Mahajan
2020	J	`jnl`	Renewal Monte Carlo: Renewal Theory-Based Reinforcement Learning. IEEE Trans. Autom. Control. Jayakumar Subramanian, Aditya Mahajan
2019	—	`conf`	Approximate information state for partially observed systems. CDC Jayakumar Subramanian, Aditya Mahajan
2019	A	`conf`	Reinforcement Learning in Stationary Mean-field Games. AAMAS Jayakumar Subramanian, Aditya Mahajan
2018	—	`conf`	On Controllability of Leader-Follower Dynamics over a Directed Graph. CDC Jayakumar Subramanian, Aditya Mahajan, Aditya A. Paranjape
2018	—	`conf`	Renewal Monte Carlo: Renewal Theory Based Reinforcement Learning. CDC Jayakumar Subramanian, Aditya Mahajan
2018	J	`jnl`	Renewal Monte Carlo: Renewal theory based reinforcement learning. CoRR Jayakumar Subramanian, Aditya Mahajan
2017	C	`conf`	Stochastic approximation based methods for computing the optimal thresholds in remote-state estimation with packet drops. ACC Jhelum Chakravorty, Jayakumar Subramanian, Aditya Mahajan