6 papers
VISTA: An End-to-End Benchmark for Visual Spec-to-Web-App Coding Agents
JunJia Guo, Yuhang Yao, Jiawei +2
We present VISTA (VIsual Spec-To-App Benchmark), a benchmark for evaluating the end-to-end web-app generation capabilities of LLM-based agents. Unlike prior code generation benchma…
Learning Coordinated Preference for Multi-Objective Multi-Agent Reinforcement Learning
Pengxin Wang, Lihao Guo, Yi Xie +3
Cooperative multi-objective multi-agent reinforcement learning (MOMARL) models team decision making under multiple, potentially conflicting objectives. In this setting, conflicts a…
COOP: Defining, Observing, and Repairing Cooperation in LLM Multi-Agent Systems
Hanqing Yang, Narjes Nourzad, Shiyu Chen +3
Many complex tasks require extended effort, diverse capabilities, or coordinated actions beyond what a single agent can provide. However, simply adding more agents does not guarant…
DIG to Heal: Scaling General-purpose Agent Collaboration via Explainable Dynamic Decision Paths
Hanqing Yang, Hyungwoo Lee, Yuhang Yao +4
The increasingly popular agentic AI paradigm promises to harness the power of multiple, general-purpose large language model (LLM) agents to collaboratively complete complex tasks.…
The Five Ws of Multi-Agent Communication: Who Talks to Whom, When, What, and Why -- A Survey from MARL to Emergent Language and LLMs
Jingdi Chen, Hanqing Yang, Zongjun Liu +1
Multi-agent sequential decision-making powers many real-world systems, from autonomous vehicles and robotics to collaborative AI assistants. In dynamic, partially observable enviro…
LLM-Powered Decentralized Generative Agents with Adaptive Hierarchical Knowledge Graph for Cooperative Planning
Hanqing Yang, Jingdi Chen, Marie Siew +2
Developing intelligent agents for long-term cooperation in dynamic open-world scenarios is a major challenge in multi-agent systems. Traditional Multi-agent Reinforcement Learning…