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Posts by Collection
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publications
Multiple Resource Management and Burst Time Prediction using Deep Reinforcement Learning
Published in Eighth International Conference on Advances in Computing, Communication and Information Technology CCIT, 2019
Recommended citation: Kumar V, Bhambri S, Shambharkar PG. Multiple resource management and burst time prediction using deep reinforcement learning. In: Eighth International Conference on advances in computing, communication and information technology CCIT, 2019, pp. 51–58. https://www.seekdl.org/conferences/paper/details/10091.html
A Survey of Black-Box Adversarial Attacks on Computer Vision Models
Published in arXiv Pre-print, 2020
Recommended citation: Bhambri, S., Muku, S., Tulasi, A., & Buduru, A. B. (2019). A survey of black-box adversarial attacks on computer vision models. arXiv preprint arXiv:1912.01667. https://arxiv.org/abs/1912.01667
Multi-objective Reinforcement Learning based approach for User-Centric Power Optimization in Smart Home Environments
Published in IEEE International Conference on Smart Data Services (SMDS), 2020
Recommended citation: S. Gupta, S. Bhambri, K. Dhingra, A. B. Buduru and P. Kumaraguru, "Multi-objective Reinforcement Learning based approach for User-Centric Power Optimization in Smart Home Environments," 2020 IEEE International Conference on Smart Data Services (SMDS), 2020, pp. 89-96, doi: 10.1109/SMDS49396.2020.00018. https://ieeexplore.ieee.org/document/9288505
Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping
Published in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
Recommended citation: Y. Zha, S. Bhambri and L. Guan, "Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping," 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, pp. 7835-7842, doi: 10.1109/IROS51168.2021.9636760. https://ieeexplore.ieee.org/document/9636760
Using Deception in Markov Game to Understand Adversarial Behaviors through a Capture-The-Flag Environment
Published in Decision and Game Theory for Security: 13th International Conference, GameSec, 2022
Recommended citation: Bhambri, Siddhant, Purv Chauhan, Frederico Araujo, Adam Doupé, and Subbarao Kambhampati. "Using Deception in Markov Game to Understand Adversarial Behaviors Through a Capture-The-Flag Environment." In International Conference on Decision and Game Theory for Security, pp. 87-106. Cham: Springer International Publishing, 2022. https://arxiv.org/pdf/2210.15011
Exploiting Unlabeled Data for Feedback Efficient Human Preference based Reinforcement Learning
Published in The AAAI Workshop on Representation Learning for Responsible Human-Centric AI (R2HCAI), and ICML - Many Facets of Preference Learning Workshop, 2023
Recommended citation: Verma, Mudit, Siddhant Bhambri, and Subbarao Kambhampati. "Exploiting Unlabeled Data for Feedback Efficient Human Preference based Reinforcement Learning." arXiv preprint arXiv:2302.08738 (2023). https://arxiv.org/abs/2302.08738
Reinforcement Learning Methods for Wordle: A POMDP/Adaptive Control Approach
Published in IEEE Conference on Games (CoG), 2023
Recommended citation: Bhambri, Siddhant, Amrita Bhattacharjee, and Dimitri Bertsekas. "Reinforcement Learning Methods for Wordle: A POMDP/Adaptive Control Approach." arXiv preprint arXiv:2211.10298 (2022). https://arxiv.org/abs/2211.10298
Preference Proxies: Evaluating Large Language Models in capturing Human Preferences in Human-AI Tasks
Published in ICML - Workshop on Theory of Mind in Communicating Agents, and Many Facets of Preference Learning Workshop, 2023
Recommended citation: Verma, Mudit, Siddhant Bhambri, and Subbarao Kambhampati. "Preference Proxies: Evaluating Large Language Models in capturing Human Preferences in Human-AI Tasks." In ICML 2023 Workshop The Many Facets of Preference-Based Learning. 2023. https://sbhambr1.github.io/files/Preference%20Proxies:%20Evaluating%20Large%20Language%20Models%20in%20capturing%20Human%20Preferences%20in%20Human-AI%20Tasks.pdf
Benchmarking Multi-Agent Preference-based Reinforcement Learning for Human-AI Teaming
Published in arXiv Pre-print, 2023
Recommended citation: Bhambri, Siddhant, Mudit Verma, Anil Murthy, and Subbarao Kambhampati. "Benchmarking Multi-Agent Preference-based Reinforcement Learning for Human-AI Teaming." arXiv preprint arXiv:2312.14292 (2023). https://arxiv.org/pdf/2312.14292
Theory of Mind abilities of Large Language Models in Human-Robot Interaction: An Illusion?
Published in Human Robot Interaction (HRI), 2024
Recommended citation: Verma, Mudit, Siddhant Bhambri, and Subbarao Kambhampati. "Theory of Mind abilities of Large Language Models in Human-Robot Interaction: An Illusion?." arXiv preprint arXiv:2401.05302 (2024). https://arxiv.org/pdf/2401.05302
On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models
Published in arXiv Pre-print, 2024
Recommended citation: Verma, Mudit, Siddhant Bhambri, and Subbarao Kambhampati. "On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models." arXiv preprint arXiv:2405.13966 (2024). https://arxiv.org/pdf/2405.13966
Efficient Reinforcement Learning via Large Language Model-based Search
Published in arXiv Pre-print, 2024
Recommended citation: Bhambri, Siddhant, et al. "Efficient Reinforcement Learning via Large Language Model-based Search." arXiv preprint arXiv:2405.15194 (2024). https://arxiv.org/abs/2405.15194
Robust Planning with LLM-Modulo Framework: Case Study in Travel Planning
Published in arXiv Pre-print, 2024
Recommended citation: Gundawar, Atharva, et al. "Robust Planning with LLM-Modulo Framework: Case Study in Travel Planning." arXiv preprint arXiv:2405.20625 (2024). https://arxiv.org/pdf/2405.20625
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Reviewer
Conference, IEEE International Conference on Intelligent Robots And Systems (IROS), 2021
Teaching Assistant: CSE 471 - Intro To AI
Undergraduate course, School of CS & AI, ASU, 2021
I was appointed as the TA for Dr. Subbarao Kambhampati’s course on Intro To AI offered in Fall ‘21.
Reviewer
Journal, IEEE Transactions on Dependable and Secure Computing (TDSC), 2021