Symbols as a lingua franca for bridging human-ai chasm for explainable and advisable ai systems S Kambhampati, S Sreedharan, M Verma, Y Zha, L Guan Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 12262 …, 2022 | 47 | 2022 |
Widening the pipeline in human-guided reinforcement learning with explanation and context-aware data augmentation L Guan, M Verma, SS Guo, R Zhang, S Kambhampati Advances in Neural Information Processing Systems 34, 21885-21897, 2021 | 38 | 2021 |
Bridging the gap: Providing post-hoc symbolic explanations for sequential decision-making problems with inscrutable representations S Sreedharan, U Soni, M Verma, S Srivastava, S Kambhampati arXiv preprint arXiv:2002.01080, 2020 | 32 | 2020 |
Explanation augmented feedback in human-in-the-loop reinforcement learning L Guan*, M Verma*, S Guo, R Zhang, S Kambhampati arXiv preprint arXiv:2006.14804, 2020 | 19 | 2020 |
Bridging the gap: Providing post-hoc symbolic explanations for sequential decision-making problems with black box simulators S Sreedharan, U Soni, M Verma, S Srivastava, S Kambhampati arXiv preprint arXiv:2002.01080, 2020 | 19 | 2020 |
Trust-aware planning: Modeling trust evolution in longitudinal human-robot interaction Z Zahedi, M Verma, S Sreedharan, S Kambhampati ICAPS 2021 Workshop on Explainable AI Planning, 2021 | 15 | 2021 |
Position: LLMs Can’t Plan, But Can Help Planning in LLM-Modulo Frameworks S Kambhampati, K Valmeekam, L Guan, M Verma, K Stechly, S Bhambri, ... Forty-first International Conference on Machine Learning, 0 | 14* | |
Fine-grained language identification with multilingual CapsNet model M Verma, AB Buduru 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM), 94-102, 2020 | 12 | 2020 |
Theory of Mind abilities of Large Language Models in Human-Robot Interaction: An Illusion? M Verma, S Bhambri, S Kambhampati arXiv preprint arXiv:2401.05302, 2024 | 10 | 2024 |
Trust-aware planning: Modeling trust evolution in iterated human-robot interaction Z Zahedi, M Verma, S Sreedharan, S Kambhampati Proceedings of the 2023 ACM/IEEE international conference on human-robot …, 2023 | 10 | 2023 |
Symbol guided hindsight priors for reward learning from human preferences M Verma, K Metcalf arXiv preprint arXiv:2210.09151, 2022 | 9 | 2022 |
Modeling the interplay between human trust and monitoring Z Zahedi, S Sreedharan, M Verma, S Kambhampati 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2022 | 8 | 2022 |
A novel framework for neural architecture search in the hill climbing domain M Verma, P Sinha, K Goyal, A Verma, S Susan 2019 IEEE Second International Conference on Artificial Intelligence and …, 2019 | 8 | 2019 |
Making smart homes smarter: optimizing energy consumption with human in the loop M Verma, S Bhambri, S Gupta, AB Buduru arXiv preprint arXiv:1912.03298, 2019 | 7 | 2019 |
Exploiting Unlabeled Data for Feedback Efficient Human Preference based Reinforcement Learning M Verma, S Bhambri, S Kambhampati arXiv preprint arXiv:2302.08738, 2023 | 6 | 2023 |
Synthesizing policies that account for human execution errors caused by state aliasing in markov decision processes S Gopalakrishnan, M Verma, S Kambhampati ICAPS 2021 Workshop on Explainable AI Planning, 2021 | 6 | 2021 |
Towards customizable reinforcement learning agents: Enabling preference specification through online vocabulary expansion U Soni, N Thakur, S Sreedharan, L Guan, M Verma, M Marquez, ... arXiv preprint arXiv:2210.15096, 2022 | 5 | 2022 |
Computing Policies That Account For The Effects Of Human Agent Uncertainty During Execution In Markov Decision Processes S Gopalakrishnan, M Verma, S Kambhampati arXiv preprint arXiv:2109.07436, 2021 | 5 | 2021 |
Advice Conformance Verification by Reinforcement Learning agents for Human-in-the-Loop M Verma, A Kharkwal, S Kambhampati arXiv preprint arXiv:2210.03455, 2022 | 4 | 2022 |
A State Augmentation based approach to Reinforcement Learning from Human Preferences M Verma, S Kambhampati arXiv preprint arXiv:2302.08734, 2023 | 3 | 2023 |