10 papers
Bayesian Partner Modelling enables Adaptive Replanning for LLM Coordination
Harsh Goel, Aditya Sai Ellendula, Vaishnav Tadiparthi +3
Multi-agent Large Language Model (LLM) systems often struggle to collaborate with new teammates whose strategies shift mid-task. Because agents execute multi-step or temporally ext…
Generative Skill Composition for LLM Agents
Xinyu Zhao, Zhen Tan, Vaishnav Tadiparthi +5
Recent LLM agents benefit from skills for solving complex tasks. Skills encapsulate modular packages of procedural knowledge and instructions for performing specialized tasks, such…
Understanding the Role of Hallucination in Reinforcement Post-Training of Multimodal Reasoning Models
Gengwei Zhang, Jie Peng, Zhen Tan +6
The recent success of reinforcement learning (RL) in large reasoning models has inspired the growing adoption of RL for post-training Multimodal Large Language Models (MLLMs) to en…
SSR: A Generic Framework for Text-Aided Map Compression for Localization
Mohammad Omama, Po-han Li, Harsh Goel +6
Mapping is crucial in robotics for localization and downstream decision-making. As robots are deployed in ever-broader settings, the maps they rely on continue to increase in size.…
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…
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…