BER-Optimized Robust Precoder Design for MIMO-OFDM Systems with Insufficient CP. - Javed Akhtar; Amrit S. Bedi; Ketan Rajawat; Aditya K. Jagannatham (GLOBECOM, 2016)

Online load scheduling under price and demand uncertainty in smart grid. - Amrit S. Bedi; Ketan Rajawat (SPCOM, 2016)

BER-Optimized Precoders for OFDM Systems With Insufficient Cyclic Prefix. - Amrit S. Bedi; Javed Akhtar; Ketan Rajawat; Aditya K. Jagannatham (IEEE Commun. Lett., 2016)

Beyond consensus and synchrony in decentralized online optimization using saddle point method. - Amrit Singh Bedi; Alec Koppel; Ketan Rajawat (ACSSC, 2017)

Optimal utilization of storage systems under real-time pricing. - Amrit S. Bedi; Md. Waseem Ahmad; Ketan Rajawat; Sandeep Anand (ICC Workshops, 2017)

Asynchronous resource allocation in distributed heterogeneous networks. - Amrit S. Bedi; Ketan Rajawat (ICC, 2017)

On Socially Optimal Traffic Flow in the Presence of Random Users. - Anant Chopra; Deepak S. Kalhan; Amrit S. Bedi; Abhishek K. Gupta; Ketan Rajawat (ANTS, 2018)

Time Varying optimization via Inexact Proximal Online Gradient Descent. - Rishabh Dixit; Amrit Singh Bedi; Ruchi Tripathi; Ketan Rajawat (ACSSC, 2018)

Asynchronous Saddle Point Method: Interference Management Through Pricing. - Amrit Singh Bedi; Alec Koppel; Ketan Rajawat (CDC, 2018)

Exact Nonparametric Decentralized Online Optimization. - Hrusikesha Pradhan; Amrit Singh Bedi; Alec Koppel; Ketan Rajawat (GlobalSIP, 2018)

Adversarial Multi-Agent Target Tracking with Inexact Online Gradient Descent. - Amrit Singh Bedi; Paban Sarma; Ketan Rajawat (ICASSP, 2018)

An Online Approach to D2D Trajectory Utility Maximization Problem. - Amrit S. Bedi; Ketan Rajawat; Marceau Coupechoux (INFOCOM, 2018)

Decentralized Asynchronous Stochastic Gradient Descent: Convergence Rate Analysis. - Amrit Singh Bedi; Hrusikesha Pradhan; Ketan Rajawat (SPCOM, 2018)

Wireless network optimization via stochastic sub-gradient descent: Rate analysis. - Amrit Singh Bedi; Ketan Rajawat (WCNC, 2018)

Tracking Moving Agents via Inexact Online Gradient Descent Algorithm. - Amrit S. Bedi; Paban Sarma; Ketan Rajawat (IEEE J. Sel. Top. Signal Process., 2018)

Network Resource Allocation via Stochastic Subgradient Descent: Convergence Rate. - Amrit Singh Bedi; Ketan Rajawat (IEEE Trans. Commun., 2018)

Asynchronous Incremental Stochastic Dual Descent Algorithm for Network Resource Allocation. - Amrit S. Bedi; Ketan Rajawat (IEEE Trans. Signal Process., 2018)

Compressed Streaming Importance Sampling for Efficient Representations of Localization Distributions. - Amrit Singh Bedi; Alec Koppel; Brian M. Sadler; Víctor Elvira (ACSSC, 2019)

Controlling the Bias-Variance Tradeoff via Coherent Risk for Robust Learning with Kernels. - Alec Koppel; Amrit S. Bedi; Ketan Rajawat (ACC, 2019)

Distributed Online Learning over Time-varying Graphs via Proximal Gradient Descent. - Rishabh Dixit; Amrit Singh Bedi; Ketan Rajawat; Alec Koppel (CDC, 2019)

Nonstationary Nonparametric Online Learning: Balancing Dynamic Regret and Model Parsimony. - Amrit Singh Bedi; Alec Koppel; Ketan Rajawat; Brian M. Sadler (CoRR, 2019)

Approximate Shannon Sampling in Importance Sampling: Nearly Consistent Finite Particle Estimates. - Alec Koppel; Amrit Singh Bedi; Victor Elvira; Brian M. Sadler (CoRR, 2019)

Optimally Compressed Nonparametric Online Learning. - Alec Koppel; Amrit Singh Bedi; Ketan Rajawat; Brian M. Sadler (CoRR, 2019)

Asynchronous Online Learning in Multi-Agent Systems With Proximity Constraints. - Amrit Singh Bedi; Alec Koppel; Ketan Rajawat (IEEE Trans. Signal Inf. Process. over Networks, 2019)

Asynchronous Saddle Point Algorithm for Stochastic Optimization in Heterogeneous Networks. - Amrit Singh Bedi; Alec Koppel; Ketan Rajawat (IEEE Trans. Signal Process., 2019)

Online Learning With Inexact Proximal Online Gradient Descent Algorithms. - Rishabh Dixit; Amrit Singh Bedi; Ruchi Tripathi; Ketan Rajawat (IEEE Trans. Signal Process., 2019)

Conservative Multi-agent Online Kernel Learning in Heterogeneous Networks. - Hrusikesha Pradhan; Amrit Singh Bedi; Alec Koppel; Ketan Rajawat (ACSSC, 2020)

Trading Dynamic Regret for Model Complexity in Nonstationary Nonparametric Optimization. - Amrit Singh Bedi; Alec Koppel; Ketan Rajawat; Brian M. Sadler (ACC, 2020)

Communication Efficient Framework for Decentralized Machine Learning. - Anis Elgabli; Jihong Park; Amrit S. Bedi; Mehdi Bennis; Vaneet Aggarwal (CISS, 2020)

Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning. - Anis Elgabli; Jihong Park; Amrit S. Bedi; Mehdi Bennis; Vaneet Aggarwal (ICASSP, 2020)

Projection Free Dynamic Online Learning. - Deepak S. Kalhan; Amrit S. Bedi; Alec Koppel; Ketan Rajawat; Abhishek K. Gupta; Adrish Banerjee (ICASSP, 2020)

Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions. - Amrit Singh Bedi; Dheeraj Peddireddy; Vaneet Aggarwal; Alec Koppel (L4DC, 2020)

Variational Policy Gradient Method for Reinforcement Learning with General Utilities. - Junyu Zhang; Alec Koppel; Amrit Singh Bedi; Csaba Szepesvári; Mengdi Wang (NeurIPS, 2020)

Efficient Gaussian Process Bandits by Believing only Informative Actions. - Amrit Singh Bedi; Dheeraj Peddireddy; Vaneet Aggarwal; Alec Koppel (CoRR, 2020)

GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning. - Anis Elgabli; Jihong Park; Amrit S. Bedi; Mehdi Bennis; Vaneet Aggarwal (J. Mach. Learn. Res., 2020)

Asynchronous and Parallel Distributed Pose Graph Optimization. - Yulun Tian; Alec Koppel; Amrit Singh Bedi; Jonathan P. How (IEEE Robotics Autom. Lett., 2020)

Optimally Compressed Nonparametric Online Learning: Tradeoffs between memory and consistency. - Alec Koppel; Amrit Singh Bedi; Ketan Rajawat; Brian M. Sadler (IEEE Signal Process. Mag., 2020)

Online Trajectory Optimization Using Inexact Gradient Feedback for Time-Varying Environments. - Mohan Krishna Nutalapati; Amrit Singh Bedi; Ketan Rajawat; Marceau Coupechoux (IEEE Trans. Signal Process., 2020)

Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning. - Alec Koppel; Amrit Singh Bedi; Bhargav Ganguly; Vaneet Aggarwal (ACSCC, 2021)

Conservative Stochastic Optimization: $ mathcal{O}(T^{-1/2})$ Optimality Gap with Zero Constraint Violation. - Zeeshan Akhtar; Amrit Singh Bedi; Ketan Rajawat (ACC, 2021)

Joint Position and Beamforming Control via Alternating Nonlinear Least-Squares with a Hierarchical Gamma Prior. - Anjaly Parayil; Amrit Singh Bedi; Alec Koppel (ACC, 2021)

Beyond Cumulative Returns via Reinforcement Learning over State-Action Occupancy Measures. - Junyu Zhang; Amrit Singh Bedi; Mengdi Wang; Alec Koppel (ACC, 2021)

Intermittent Communications in Decentralized Shadow Reward Actor-Critic. - Amrit Singh Bedi; Alec Koppel; Mengdi Wang; Junyu Zhang (CDC, 2021)

Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent. - Anis Elgabli; Chaouki Ben Issaid; Amrit S. Bedi; Mehdi Bennis; Vaneet Aggarwal (GLOBECOM, 2021)

A Dynamical Systems Perspective on Online Bayesian Nonparametric Estimators with Adaptive Hyperparameters. - Alec Koppel; Amrit S. Bedi; Vikram Krishnamurthy (ICASSP, 2021)

Wasserstein-Splitting Gaussian Process Regression for Heterogeneous Online Bayesian Inference. - Michael E. Kepler; Alec Koppel; Amrit Singh Bedi; Daniel J. Stilwell (IROS, 2021)

MARL with General Utilities via Decentralized Shadow Reward Actor-Critic. - Junyu Zhang; Amrit Singh Bedi; Mengdi Wang; Alec Koppel (CoRR, 2021)

Projection-Free Algorithm for Stochastic Bi-level Optimization. - Zeeshan Akhtar; Amrit Singh Bedi; Srujan Teja Thomdapu; Ketan Rajawat (CoRR, 2021)

Cautious Reinforcement Learning via Distributional Risk in the Dual Domain. - Junyu Zhang; Amrit Singh Bedi; Mengdi Wang; Alec Koppel (IEEE J. Sel. Areas Inf. Theory, 2021)

Online Learning Over Dynamic Graphs via Distributed Proximal Gradient Algorithm. - Rishabh Dixit; Amrit Singh Bedi; Ketan Rajawat (IEEE Trans. Autom. Control., 2021)

Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning. - Anis Elgabli; Jihong Park; Amrit Singh Bedi; Chaouki Ben Issaid; Mehdi Bennis; Vaneet Aggarwal (IEEE Trans. Commun., 2021)

Adaptive Kernel Learning in Heterogeneous Networks. - Hrusikesha Pradhan; Amrit Singh Bedi; Alec Koppel; Ketan Rajawat (IEEE Trans. Signal Inf. Process. over Networks, 2021)

Conservative Stochastic Optimization With Expectation Constraints. - Zeeshan Akhtar; Amrit Singh Bedi; Ketan Rajawat (IEEE Trans. Signal Process., 2021)

Nonparametric Compositional Stochastic Optimization for Risk-Sensitive Kernel Learning. - Amrit Singh Bedi; Alec Koppel; Ketan Rajawat; Panchajanya Sanyal (IEEE Trans. Signal Process., 2021)

Dynamic Online Learning via Frank-Wolfe Algorithm. - Deepak S. Kalhan; Amrit Singh Bedi; Alec Koppel; Ketan Rajawat; Hamed Hassani; Abhishek K. Gupta; Adrish Banerjee (IEEE Trans. Signal Process., 2021)

Nearly Consistent Finite Particle Estimates in Streaming Importance Sampling. - Alec Koppel; Amrit Singh Bedi; Brian M. Sadler; Víctor Elvira (IEEE Trans. Signal Process., 2021)

Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. - Qinbo Bai; Amrit Singh Bedi; Mridul Agarwal; Alec Koppel; Vaneet Aggarwal (AAAI, 2022)

Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic. - Junyu Zhang; Amrit Singh Bedi; Mengdi Wang; Alec Koppel (AAAI, 2022)

Fast Distributed Beamforming without Receiver Feedback. - Kushal Chakrabarti; Amrit S. Bedi; Fikadu T. Dagefu; Jeffrey N. Twigg; Nikhil Chopra (IEEECONF, 2022)

Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming. - Alec Koppel; Amrit Singh Bedi; Bhargav Ganguly; Vaneet Aggarwal (CDC, 2022)

HTRON: Efficient Outdoor Navigation with Sparse Rewards via Heavy Tailed Adaptive Reinforce Algorithm. - Kasun Weerakoon; Souradip Chakraborty; Nare Karapetyan; Adarsh Jagan Sathyamoorthy; Amrit S. Bedi; Dinesh Manocha (CoRL, 2022)

On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces. - Amrit Singh Bedi; Souradip Chakraborty; Anjaly Parayil; Brian M. Sadler; Pratap Tokekar; Alec Koppel (ICML, 2022)

FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning. - Anis Elgabli; Chaouki Ben Issaid; Amrit Singh Bedi; Ketan Rajawat; Mehdi Bennis; Vaneet Aggarwal (ICML, 2022)

DC-MRTA: Decentralized Multi-Robot Task Allocation and Navigation in Complex Environments. - Aakriti Agrawal; Senthil Hariharan Arul; Amrit Singh Bedi; Dinesh Manocha (IROS, 2022)

Distributed Riemannian Optimization with Lazy Communication for Collaborative Geometric Estimation. - Yulun Tian; Amrit Singh Bedi; Alec Koppel; Miguel Calvo-Fullana; David M. Rosen; Jonathan P. How (IROS, 2022)

Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policies. - Souradip Chakraborty; Amrit Singh Bedi; Alec Koppel; Pratap Tokekar; Dinesh Manocha (CoRR, 2022)

FedBC: Calibrating Global and Local Models via Federated Learning Beyond Consensus. - Amrit Singh Bedi; Chen Fan; Alec Koppel; Anit Kumar Sahu; Brian M. Sadler; Furong Huang; Dinesh Manocha (CoRR, 2022)

DMCA: Dense Multi-agent Navigation using Attention and Communication. - Senthil Hariharan Arul; Amrit Singh Bedi; Dinesh Manocha (CoRR, 2022)

Projection-Free Stochastic Bi-Level Optimization. - Zeeshan Akhtar; Amrit Singh Bedi; Srujan Teja Thomdapu; Ketan Rajawat (IEEE Trans. Signal Process., 2022)

Escaping Saddle Points for Successive Convex Approximation. - Amrit Singh Bedi; Ketan Rajawat; Vaneet Aggarwal; Alec Koppel (IEEE Trans. Signal Process., 2022)

Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm. - Qinbo Bai; Amrit Singh Bedi; Vaneet Aggarwal (AAAI, 2023)

Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning. - Souradip Chakraborty; Amrit Singh Bedi; Pratap Tokekar; Alec Koppel; Brian M. Sadler; Furong Huang; Dinesh Manocha (AAAI, 2023)

Bi-Level Nonstationary Kernels for Online Gaussian Process Regression. - Hans He; Alec Koppel; Amrit Singh Bedi; Mazen Farhood; Daniel J. Stilwell (CASE, 2023)

Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement Learning. - Xiyang Wu; Rohan Chandra; Tianrui Guan; Amrit S. Bedi; Dinesh Manocha (CoRL, 2023)

SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication. - Marco Bornstein; Tahseen Rabbani; Evan Wang; Amrit S. Bedi; Furong Huang (ICLR, 2023)

STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning. - Souradip Chakraborty; Amrit S. Bedi; Alec Koppel; Mengdi Wang; Furong Huang; Dinesh Manocha (ICML, 2023)

Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic. - Wesley A. Suttle; Amrit S. Bedi; Bhrij Patel; Brian M. Sadler; Alec Koppel; Dinesh Manocha (ICML, 2023)

RTAW: An Attention Inspired Reinforcement Learning Method for Multi-Robot Task Allocation in Warehouse Environments. - Aakriti Agrawal; Amrit Singh Bedi; Dinesh Manocha (ICRA, 2023)

Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policy Optimization. - Souradip Chakraborty; Amrit Singh Bedi; Kasun Weerakoon; Prithvi Poddar; Alec Koppel; Pratap Tokekar; Dinesh Manocha (ICRA, 2023)

Decentralized Multi-agent Exploration with Limited Inter-agent Communications. - Hans He; Alec Koppel; Amrit Singh Bedi; Daniel J. Stilwell; Mazen Farhood; Benjamin Biggs (ICRA, 2023)

RE-MOVE: An Adaptive Policy Design Approach for Dynamic Environments via Language-Based Feedback. - Souradip Chakraborty; Kasun Weerakoon; Prithvi Poddar; Pratap Tokekar; Amrit Singh Bedi; Dinesh Manocha (CoRR, 2023)

On the Possibilities of AI-Generated Text Detection. - Souradip Chakraborty; Amrit Singh Bedi; Sicheng Zhu; Bang An 001; Dinesh Manocha; Furong Huang (CoRR, 2023)

Ada-NAV: Adaptive Trajectory-Based Sample Efficient Policy Learning for Robotic Navigation. - Bhrij Patel; Kasun Weerakoon; Wesley A. Suttle; Alec Koppel; Brian M. Sadler; Amrit Singh Bedi; Dinesh Manocha (CoRR, 2023)

iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement Learning. - Xiyang Wu; Rohan Chandra; Tianrui Guan; Amrit Singh Bedi; Dinesh Manocha (CoRR, 2023)

On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization. - Mudit Gaur; Amrit Singh Bedi; Di Wang 015; Vaneet Aggarwal (CoRR, 2023)

Aligning Agent Policy with Externalities: Reward Design via Bilevel RL. - Souradip Chakraborty; Amrit Singh Bedi; Alec Koppel; Dinesh Manocha; Huazheng Wang; Furong Huang; Mengdi Wang (CoRR, 2023)

LANCAR: Leveraging Language for Context-Aware Robot Locomotion in Unstructured Environments. - Chak Lam Shek; Xiyang Wu; Dinesh Manocha; Pratap Tokekar; Amrit Singh Bedi (CoRR, 2023)

RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation. - Marco Bornstein; Amrit Singh Bedi; Anit Kumar Sahu; Furqan Khan; Furong Huang (CoRR, 2023)

Towards Possibilities & Impossibilities of AI-generated Text Detection: A Survey. - Soumya Suvra Ghosal; Souradip Chakraborty; Jonas Geiping; Furong Huang; Dinesh Manocha; Amrit Singh Bedi (CoRR, 2023)

REBEL: A Regularization-Based Solution for Reward Overoptimization in Reinforcement Learning from Human Feedback. - Souradip Chakraborty; Amisha Bhaskar; Anukriti Singh; Pratap Tokekar; Dinesh Manocha; Amrit Singh Bedi (CoRR, 2023)

A Survey on the Possibilities & Impossibilities of AI-generated Text Detection. - Soumya Suvra Ghosal; Souradip Chakraborty; Jonas Geiping; Furong Huang; Dinesh Manocha; Amrit S. Bedi (Trans. Mach. Learn. Res., 2023)

PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback. - Souradip Chakraborty; Amrit Singh Bedi; Alec Koppel; Huazheng Wang; Dinesh Manocha; Mengdi Wang; Furong Huang (ICLR, 2024)

Position: On the Possibilities of AI-Generated Text Detection. - Souradip Chakraborty; Amrit S. Bedi; Sicheng Zhu; Bang An 001; Dinesh Manocha; Furong Huang (ICML, 2024)

MaxMin-RLHF: Alignment with Diverse Human Preferences. - Souradip Chakraborty; Jiahao Qiu; Hui Yuan 002; Alec Koppel; Dinesh Manocha; Furong Huang; Amrit S. Bedi; Mengdi Wang (ICML, 2024)

Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization. - Mudit Gaur; Amrit S. Bedi; Di Wang 015; Vaneet Aggarwal (ICML, 2024)

Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles. - Bhrij Patel; Wesley A. Suttle; Alec Koppel; Vaneet Aggarwal; Brian M. Sadler; Dinesh Manocha; Amrit S. Bedi (ICML, 2024)

PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling. - Utsav Singh; Wesley A. Suttle; Brian M. Sadler; Vinay P. Namboodiri; Amrit S. Bedi (ICML, 2024)

When, What, and with Whom to Communicate: Enhancing RL-based Multi-Robot Navigation through Selective Communication. - Senthil Hariharan Arul; Amrit Singh Bedi; Dinesh Manocha (IROS, 2024)

LANCAR: Leveraging Language for Context-Aware Robot Locomotion in Unstructured Environments. - Chak Lam Shek; Xiyang Wu; Wesley A. Suttle; Carl E. Busart; Erin G. Zaroukian; Dinesh Manocha; Pratap Tokekar; Amrit Singh Bedi (IROS, 2024)

TrustNavGPT: Modeling Uncertainty to Improve Trustworthiness of Audio-Guided LLM-Based Robot Navigation. - Xingpeng Sun; Yiran Zhang; Xindi Tang; Amrit Singh Bedi; Aniket Bera (IROS, 2024)

FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? - Marco Bornstein; Amrit Singh Bedi; Abdirisak Mohamed; Furong Huang (NeurIPS, 2024)

Transfer Q-star : Principled Decoding for LLM Alignment. - Souradip Chakraborty; Soumya Suvra Ghosal; Ming Yin 003; Dinesh Manocha; Mengdi Wang; Amrit Singh Bedi; Furong Huang (NeurIPS, 2024)

Beyond Text: Improving LLM's Decision Making for Robot Navigation via Vocal Cues. - Xingpeng Sun; Haoming Meng; Souradip Chakraborty; Amrit Singh Bedi; Aniket Bera (CoRR, 2024)

MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences. - Souradip Chakraborty; Jiahao Qiu; Hui Yuan 002; Alec Koppel; Furong Huang; Dinesh Manocha; Amrit Singh Bedi; Mengdi Wang (CoRR, 2024)

On the Safety Concerns of Deploying LLMs/VLMs in Robotics: Highlighting the Risks and Vulnerabilities. - Xiyang Wu; Ruiqi Xian; Tianrui Guan; Jing Liang 006; Souradip Chakraborty; Fuxiao Liu; Brian M. Sadler; Dinesh Manocha; Amrit Singh Bedi (CoRR, 2024)

Right Place, Right Time! Towards ObjectNav for Non-Stationary Goals. - Vishnu Sashank Dorbala; Bhrij Patel; Amrit Singh Bedi; Dinesh Manocha (CoRR, 2024)

Global Optimality without Mixing Time Oracles in Average-reward RL via Multi-level Actor-Critic. - Bhrij Patel; Wesley A. Suttle; Alec Koppel; Vaneet Aggarwal; Brian M. Sadler; Amrit Singh Bedi; Dinesh Manocha (CoRR, 2024)

Embodied Question Answering via Multi-LLM Systems. - Bhrij Patel; Vishnu Sashank Dorbala; Dinesh Manocha; Amrit Singh Bedi (CoRR, 2024)

SAIL: Self-Improving Efficient Online Alignment of Large Language Models. - Mucong Ding; Souradip Chakraborty; Vibhu Agrawal; Zora Che; Alec Koppel; Mengdi Wang; Amrit S. Bedi; Furong Huang (CoRR, 2024)

CAT: Caution Aware Transfer in Reinforcement Learning via Distributional Risk. - Mohamad Fares El Hajj Chehade; Amrit Singh Bedi; Amy Zhang 001; Hao Zhu (CoRR, 2024)

Auction-Based Regulation for Artificial Intelligence. - Marco Bornstein; Zora Che; Suhas Julapalli; Abdirisak Mohamed; Amrit Singh Bedi; Furong Huang (CoRR, 2024)

AIME: AI System Optimization via Multiple LLM Evaluators. - Bhrij Patel; Souradip Chakraborty; Wesley A. Suttle; Mengdi Wang; Amrit Singh Bedi; Dinesh Manocha (CoRR, 2024)

On the Sample Complexity of a Policy Gradient Algorithm with Occupancy Approximation for General Utility Reinforcement Learning. - Anas Barakat; Souradip Chakraborty; Peihong Yu; Pratap Tokekar; Amrit Singh Bedi (CoRR, 2024)

EfficientEQA: An Efficient Approach for Open Vocabulary Embodied Question Answering. - Kai Cheng; Zhengyuan Li; Xingpeng Sun; Byung-Cheol Min; Amrit Singh Bedi; Aniket Bera (CoRR, 2024)

Hierarchical Preference Optimization: Learning to achieve goals via feasible subgoals prediction. - Utsav Singh; Souradip Chakraborty; Wesley A. Suttle; Brian M. Sadler; Anit Kumar Sahu; Mubarak Shah; Vinay P. Namboodiri; Amrit Singh Bedi (CoRR, 2024)

LIAR: Leveraging Alignment (Best-of-N) to Jailbreak LLMs in Seconds. - James Beetham; Souradip Chakraborty; Mengdi Wang; Furong Huang; Amrit Singh Bedi; Mubarak Shah (CoRR, 2024)

On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control. - Amrit Singh Bedi; Anjaly Parayil; Junyu Zhang; Mengdi Wang; Alec Koppel (J. Mach. Learn. Res., 2024)

Beyond Text: Utilizing Vocal Cues to Improve Decision Making in LLMs for Robot Navigation Tasks. - Xingpeng Sun; Haoming Meng; Souradip Chakraborty; Amrit S. Bedi; Aniket Bera (Trans. Mach. Learn. Res., 2024)

Align-Pro: A Principled Approach to Prompt Optimization for LLM Alignment. - Prashant Trivedi; Souradip Chakraborty; Avinash Reddy; Vaneet Aggarwal; Amrit Singh Bedi; George K. Atia (AAAI, 2025)

Immune: Improving Safety Against Jailbreaks in Multi-modal LLMs via Inference-Time Alignment. - Soumya Suvra Ghosal; Souradip Chakraborty; Vaibhav Singh; Tianrui Guan; Mengdi Wang; Ahmad Beirami; Furong Huang; Alvaro Velasquez; Dinesh Manocha; Amrit Singh Bedi (CVPR, 2025)

Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning. - Peihong Yu; Manav Mishra; Alec Koppel; Carl E. Busart; Priya Narayan; Dinesh Manocha; Amrit Singh Bedi; Pratap Tokekar (Trans. Mach. Learn. Res., 2025)

BalancedDPO: Adaptive Multi-Metric Alignment. - Dipesh Tamboli; Souradip Chakraborty; Aditya Malusare; Biplab Banerjee; Amrit Singh Bedi; Vaneet Aggarwal (CoRR, 2025)

VARP: Reinforcement Learning from Vision-Language Model Feedback with Agent Regularized Preferences. - Anukriti Singh; Amisha Bhaskar; Peihong Yu; Souradip Chakraborty; Ruthwik Dasyam; Amrit Singh Bedi; Pratap Tokekar (CoRR, 2025)

On The Sample Complexity Bounds In Bilevel Reinforcement Learning. - Mudit Gaur; Amrit Singh Bedi; Raghu Pasupathu; Vaneet Aggarwal (CoRR, 2025)

Learning Multi-Robot Coordination through Locality-Based Factorized Multi-Agent Actor-Critic Algorithm. - Chak Lam Shek; Amrit Singh Bedi; Anjon Basak; Ellen R. Novoseller; Nicholas R. Waytowich; Priya Narayanan; Dinesh Manocha; Pratap Tokekar (CoRR, 2025)

Regret and Belief Complexity Tradeoff in Gaussian Process Bandits via Information Thresholding. - Amrit Singh Bedi; Dheeraj Peddireddy; Vaneet Aggarwal; Brian M. Sadler; Alec Koppel (IEEE Trans. Artif. Intell., 2025)

Review, Refine, Repeat: Understanding Iterative Decoding of AI Agents with Dynamic Evaluation and Selection. - Souradip Chakraborty; Mohammadreza Pourreza; Ruoxi Sun 002; Yiwen Song; Nino Scherrer; Furong Huang; Amrit Singh Bedi; Ahmad Beirami; Jindong Gu; Hamid Palangi; Tomas Pfister (CoRR, 2025)

Sample Complexity of Diffusion Model Training Without Empirical Risk Minimizer Access. - Mudit Gaur; Prashant Trivedi; Sasidhar Kunapuli; Amrit Singh Bedi; Vaneet Aggarwal (CoRR, 2025)

Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time. - Mohamad Fares El Hajj Chehade; Soumya Suvra Ghosal; Souradip Chakraborty; Avinash Reddy; Dinesh Manocha; Hao Zhu; Amrit Singh Bedi (CoRR, 2025)

Does Thinking More always Help? Understanding Test-Time Scaling in Reasoning Models. - Soumya Suvra Ghosal; Souradip Chakraborty; Avinash Reddy; Yifu Lu; Mengdi Wang; Dinesh Manocha; Furong Huang; Mohammad Ghavamzadeh; Amrit Singh Bedi (CoRR, 2025)

Leveraging Pre-Trained Visual Models for AI-Generated Video Detection. - Keerthi Veeramachaneni; Praveen Tirupattur; Amrit Singh Bedi; Mubarak Shah (CoRR, 2025)

PROPS: Progressively Private Self-alignment of Large Language Models. - Noel Teku; Fengwei Tian; Payel Bhattacharjee; Souradip Chakraborty; Amrit Singh Bedi; Ravi Tandon (CoRR, 2025)