activity
20182026
most citedImplementation and Evaluation of a Cooperative Vehicle-to-Pedestrian Safety Application

83 citations · 114 across the 21 of their papers we have counts for

collaborators

21 papers

cs.LG2026

Learning Robust Reasoning through Guided Adversarial Self-Play

Shuozhe Li, Vaishnav Tadiparthi, Kwonjoon Lee +6

Reinforcement learning from verifiable rewards (RLVR) produces strong reasoning models, yet they can fail catastrophically when the conditioning context is fallible (e.g., corrupte…

cs.AI2025

Metacognitive Self-Correction for Multi-Agent System via Prototype-Guided Next-Execution Reconstruction

Xu Shen, Qi Zhang, Song Wang +8

Large Language Model based multi-agent systems (MAS) excel at collaborative problem solving but remain brittle to cascading errors: a single faulty step can propagate across agents…

cs.RO2025

SMART-Merge Planner: A Safe Merging and Real-Time Motion Planner for Autonomous Highway On-Ramp Merging

Toktam Mohammadnejad, Jovin D'sa, Behdad Chalaki +2

Merging onto a highway is a complex driving task that requires identifying a safe gap, adjusting speed, often interactions to create a merging gap, and completing the merge maneuve…

cs.MA2025★ 1 cited

R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning

Harsh Goel, Mohammad Omama, Behdad Chalaki +3

Multi-agent reinforcement learning (MARL) has achieved significant progress in large-scale traffic control, autonomous vehicles, and robotics. Drawing inspiration from biological s…

cs.AI2025★ 1 cited

Human-AI Collaboration: Trade-offs Between Performance and Preferences

Lukas William Mayer, Sheer Karny, Jackie Ayoub +4

Despite the growing interest in collaborative AI, designing systems that seamlessly integrate human input remains a major challenge. In this study, we developed a task to systemati…

cs.RO2025

Dual Control for Interactive Autonomous Merging with Model Predictive Diffusion

Jacob Knaup, Jovin D'sa, Behdad Chalaki +3

Interactive decision-making is essential in applications such as autonomous driving, where the agent must infer the behavior of nearby human drivers while planning in real-time. Tr…