👇 Follow our official account and selectStar, to receive the latest insights daily Abstract Embodied Intelligence is a cutting-edge field at the intersection of artificial intelligence and robotics, emphasizing that agents achieve autonomous learning and evolution through dynamic interactions with their bodies and environments, with the core focus on the deep integration of perception, action, … Read more
From single agents to workflows, we have now entered the era of multi-agent systems. Multi-agent systems essentially involve multiple agents collaborating under the guidance of a large model to complete user tasks. In this context, various agent architectures have emerged, such as centralized, decentralized, and hierarchical structures. This article analyzes the multi-agent design under the … Read more
Cover Image: nice view｜Source: Hailey I enjoy learning with “questions and curiosity”, which helps to systematize and solidify knowledge rather than just accumulating information. Follow this series of articles to explore 11 questions, which will greatly assist you in familiarizing yourself with Agent and Multi-agent technology. The next article will discuss the industry applications of … Read more
When ChatGPT first emerged, there were numerous practices involving multi-agent systems in the community. The idea was quite natural: since the thinking patterns of large models resemble human cognition, could the ultimate goal be to use more large models to mimic a team and accomplish more complex tasks? However, from practical tests, compared to a … Read more
Datawhale Open Source Open Source Contribution: Handy-Multi-Agent Team Introduction “Handy-Multi-Agent” is a practical tutorial that guides you step by step from the basic single-agent model to complex multi-agent systems, focusing on practical applications. This project is based on the leading domestic multi-agent framework CAMEL, which not only deeply analyzes the various components of an agent … Read more
Imagine asking an LLM, “Did Aristotle use a laptop?” It might seriously fabricate a reason: “There was already wireless internet in ancient Greece…” This phenomenon of “seriously nonsense” is what we call the LLM’s “hallucination.” Paper: Meta-Thinking in LLMs via Multi-Agent Reinforcement Learning: A Survey Link: https://arxiv.org/pdf/2504.14520 The paper points out that meta-thinking— the ability … Read more
This article is from the public account: Jin Qiu Ji, reproduced for academic/technical sharing. If there is any infringement, please contact us to delete the article. Original link: https://mp.weixin.qq.com/s/xHXmf3yXFwFs5Jqk2vIJVw As agents are deployed into deeper waters, the tasks they face increasingly demand deep reasoning and multi-step interactions, making single-agent architectures often inadequate. Multi-Agent systems are … Read more
In the field of artificial intelligence, with the rise of large language models (LLMs), AI Agents are becoming the most notable technology hotspot of 2025. Unlike ordinary AI applications, AI Agents possess the ability to think independently, perceive their environment, and execute complex tasks, reshaping our understanding of artificial intelligence. This article will provide a … Read more
Why do multi-agent LLM systems fail? Abstract Despite the growing enthusiasm for multi-agent systems (MAS), which consist of multiple LLM agents collaborating to complete tasks, their performance improvements in popular benchmark tests remain minimal compared to single-agent frameworks. This gap highlights the necessity of analyzing the challenges that hinder the efficiency of MAS. In this … Read more
Research Background image.png|550 Research Question The problem this paper aims to address is the minimal performance improvement of Multi-Agent Large Language Model (LLM) systems (referred to as MAS) compared to single-agent frameworks. Despite the potential of MAS in handling complex multi-step tasks and interacting with dynamic environments, their accuracy or performance improvements remain limited in … Read more