4 citations · 14 across the 11 of their papers we have counts for
11 papers
VISTA: An End-to-End Benchmark for Visual Spec-to-Web-App Coding Agents
JunJia Guo, Yuhang Yao, Jiawei +4
Coding agents can now build applications from design mockups, but a screen that looks right is not an application that works. Existing benchmarks either score visual reconstruction…
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…
RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space
Jingdi Chen, Hanhan Zhou, Yongsheng Mei +4
Deep Reinforcement Learning (DRL) algorithms have achieved great success in solving many challenging tasks while their black-box nature hinders interpretability and real-world appl…
Real-time Network Intrusion Detection via Decision Transformers
Jingdi Chen, Hanhan Zhou, Yongsheng Mei +3
Many cybersecurity problems that require real-time decision-making based on temporal observations can be abstracted as a sequence modeling problem, e.g., network intrusion detectio…
RIDE: Real-time Intrusion Detection via Explainable Machine Learning Implemented in a Memristor Hardware Architecture
Jingdi Chen, Lei Zhang, Joseph Riem +3
Deep Learning (DL) based methods have shown great promise in network intrusion detection by identifying malicious network traffic behavior patterns with high accuracy, but their ap…
RGMComm: Return Gap Minimization via Discrete Communications in Multi-Agent Reinforcement Learning
Jingdi Chen, Tian Lan, Carlee Joe-Wong
Communication is crucial for solving cooperative Multi-Agent Reinforcement Learning tasks in partially observable Markov Decision Processes. Existing works often rely on black-box…
Learning Multi-agent Skills for Tabular Reinforcement Learning using Factor Graphs
Jiayu Chen, Jingdi Chen, Tian Lan +1
Covering skill (a.k.a., option) discovery has been developed to improve the exploration of reinforcement learning in single-agent scenarios with sparse reward signals, through conn…