AI Agent capabilities are largely hidden within the Prompt, which can be said to determine the behavioral guidelines of the agent. It serves as the agent’s “behavior guide,” defining roles, tasks, and decision-making logic. Without a good Prompt, even the strongest model is like a “headless fly”; conversely, a precise Prompt can liberate the agent … Read more
Research: Multi-Agent Systems, Editor: PaperAgent In multi-agent systems (MAS: multi-agent systems), designing effective prompts and topologies poses challenges, as individual agents may be sensitive to prompts, and manually designing topologies requires extensive experimentation. Paper link: https://arxiv.org/pdf/2502.02533 Paper Title: Multi-Agent Design: Optimizing Agents with Better Prompts and Topologies To automate the entire design process, Google & … Read more
MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP graduate students, university professors, and corporate researchers.The vision of the community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for beginners.Research | Multi-Agent SystemsEditor | … Read more
Datawhale shares Research: Multi-Agent Systems, Editor: PaperAgent In multi-agent systems (MAS: multi-agent systems), designing effective prompts and topologies is challenging, as individual agents may be sensitive to prompts, and manually designing topologies requires extensive experimentation. Paper link: https://arxiv.org/pdf/2502.02533 Paper title: Multi-Agent Design: Optimizing Agents with Better Prompts and Topologies To automate the entire design process, … Read more