71 citations · 88 across the 20 of their papers we have counts for
23 papers
MASBench: Benchmarking LLM-based Multi-Agent Collaboration under Partial Observability
Qizhi Chu, Zekai Yu, Sijie Wen +5
Large language models (LLMs) have progressively evolved into the core of autonomous agents. Building on this progress, LLM-based multi-agent systems (MAS) coordinate multiple agent…
PhysX-CoT: Structured Physical Reasoning from a Single Image to Simulation-Ready 3D Assets
Jie Huang, Xiaohe Li, Jiahao Li +6
Simulation-ready 3D assets are central to robotics and embodied AI. Generating them from a single image is usually framed as a vision-language model that emits a serialized asset f…
Lingjing: A Simulation Testbed for Multi-Agent Embodied Tasks in Open-Ended Cities
Xiaohe Li, Yiru Wang, Junhao Fan +6
Urban embodied intelligence requires coordination among heterogeneous agents (e.g., UAVs, ground robots, and autonomous vehicles) in dynamic cities. Simulators therefore provide a…
DataMaster: Data-Centric Autonomous AI Research
Yaxin Du, Xiyuan Yang, Zhifan Zhou +12
As model families, training recipes, and compute budgets become increasingly standardized, further gains in machine learning systems depend increasingly on data. Yet data engineeri…
Multi-Agent Reinforcement Learning with Submodular Reward
Wenjing Chen, Chengyuan Qian, Shuo Xing +2
In this paper, we study cooperative multi-agent reinforcement learning (MARL) where the joint reward exhibits submodularity, which is a natural property capturing diminishing margi…
AppCopilot: Toward General, Accurate, Long-Horizon, and Efficient Mobile Agent
Jingru Fan, Yufan Dang, Jingyao Wu +5
With the raid evolution of large language models and multimodal models, the mobile-agent landscape has proliferated without converging on the fundamental challenges. This paper ide…
Cross-Task Experiential Learning on LLM-based Multi-Agent Collaboration
Yilong Li, Chen Qian, Yu Xia +12
Large Language Model-based multi-agent systems (MAS) have shown remarkable progress in solving complex tasks through collaborative reasoning and inter-agent critique. However, exis…
Co-Saving: Resource Aware Multi-Agent Collaboration for Software Development
Rennai Qiu, Chen Qian, Ran Li +9
Recent advancements in Large Language Models (LLMs) and autonomous agents have demonstrated remarkable capabilities across various domains. However, standalone agents frequently en…
Multi-Agent Collaboration via Evolving Orchestration
Yufan Dang, Chen Qian, Xueheng Luo +11
Large language models (LLMs) have achieved remarkable results across diverse downstream tasks, but their monolithic nature restricts scalability and efficiency in complex problem-s…
GraphTeam: Facilitating Large Language Model-based Graph Analysis via Multi-Agent Collaboration
Xin Li, Qizhi Chu, Yubin Chen +7
Graphs are widely used for modeling relational data in real-world scenarios, such as social networks and urban computing. Existing LLM-based graph analysis approaches either integr…
Distance between Relevant Information Pieces Causes Bias in Long-Context LLMs
Runchu Tian, Yanghao Li, Yuepeng Fu +10
Positional bias in large language models (LLMs) hinders their ability to effectively process long inputs. A prominent example is the "lost in the middle" phenomenon, where LLMs str…
Optima: Optimizing Effectiveness and Efficiency for LLM-Based Multi-Agent System
Weize Chen, Jiarui Yuan, Chen Qian +3
Large Language Model (LLM) based multi-agent systems (MAS) show remarkable potential in collaborative problem-solving, yet they still face critical challenges: low communication ef…
Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models
Xin Li, Weize Chen, Qizhi Chu +9
The need to analyze graphs is ubiquitous across various fields, from social networks to biological research and recommendation systems. Therefore, enabling the ability of large lan…
Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence
Weize Chen, Ziming You, Ran Li +7
The rapid advancement of large language models (LLMs) has paved the way for the development of highly capable autonomous agents. However, existing multi-agent frameworks often stru…
Autonomous Agents for Collaborative Task under Information Asymmetry
Wei Liu, Chenxi Wang, Yifei Wang +7
Large Language Model Multi-Agent Systems (LLM-MAS) have achieved great progress in solving complex tasks. It performs communication among agents within the system to collaborativel…
Multi-Agent Collaboration via Cross-Team Orchestration
Zhuoyun Du, Chen Qian, Wei Liu +9
Large Language Models (LLMs) have significantly impacted various domains, especially through organized LLM-driven autonomous agents. A representative scenario is in software develo…
Scaling Large Language Model-based Multi-Agent Collaboration
Chen Qian, Zihao Xie, YiFei Wang +9
Recent breakthroughs in large language model-driven autonomous agents have revealed that multi-agent collaboration often surpasses each individual through collective reasoning. Ins…
Iterative Experience Refinement of Software-Developing Agents
Chen Qian, Jiahao Li, Yufan Dang +8
Autonomous agents powered by large language models (LLMs) show significant potential for achieving high autonomy in various scenarios such as software development. Recent research…
Beyond Natural Language: LLMs Leveraging Alternative Formats for Enhanced Reasoning and Communication
Weize Chen, Chenfei Yuan, Jiarui Yuan +6
Natural language (NL) has long been the predominant format for human cognition and communication, and by extension, has been similarly pivotal in the development and application of…
Experiential Co-Learning of Software-Developing Agents
Chen Qian, Yufan Dang, Jiahao Li +9
Recent advancements in large language models (LLMs) have brought significant changes to various domains, especially through LLM-driven autonomous agents. A representative scenario…
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
Weize Chen, Yusheng Su, Jingwei Zuo +13
Autonomous agents empowered by Large Language Models (LLMs) have undergone significant improvements, enabling them to generalize across a broad spectrum of tasks. However, in real-…
ChatDev: Communicative Agents for Software Development
Chen Qian, Wei Liu, Hongzhang Liu +11
Software development is a complex task that necessitates cooperation among multiple members with diverse skills. Numerous studies used deep learning to improve specific phases in a…
The 2nd Place Solution for 2023 Waymo Open Sim Agents Challenge
Cheng Qian, Di Xiu, Minghao Tian
In this technical report, we present the 2nd place solution of 2023 Waymo Open Sim Agents Challenge (WOSAC)[4]. We propose a simple yet effective autoregressive method for simulati…