TodyComm: Task-Oriented Dynamic Communication for Multi-Round LLM-based Multi-Agent System
📰 ArXiv cs.AI
Learn how TodyComm enables dynamic communication in multi-round LLM-based multi-agent systems for improved collaboration
Action Steps
- Implement TodyComm in your multi-agent system to enable dynamic communication
- Configure the system to adapt to changing agent roles across rounds
- Test the system's performance in various scenarios with dynamic adversary, task progression, or time-varying constraints
- Compare the results with fixed communication topology methods
- Apply TodyComm to real-world applications with multiple rounds and dynamic constraints
Who Needs to Know This
Researchers and developers working on LLM-based multi-agent systems can benefit from this knowledge to improve their system's performance and adaptability
Key Insight
💡 Dynamic communication topology can significantly improve the performance of multi-round LLM-based multi-agent systems
Share This
🤖 Improve collaboration in LLM-based multi-agent systems with TodyComm's dynamic communication! 📢
Full Article
Title: TodyComm: Task-Oriented Dynamic Communication for Multi-Round LLM-based Multi-Agent System
Abstract:
arXiv:2602.03688v2 Announce Type: replace Abstract: Multi-round LLM-based multi-agent systems rely on effective communication structures to support collaboration across rounds. However, most existing methods employ a fixed communication topology during inference, which falls short in many realistic applications where the agents' roles may change \textit{across rounds} due to dynamic adversary, task progression, or time-varying constraints such as communication bandwidth. In this paper, we propos
Abstract:
arXiv:2602.03688v2 Announce Type: replace Abstract: Multi-round LLM-based multi-agent systems rely on effective communication structures to support collaboration across rounds. However, most existing methods employ a fixed communication topology during inference, which falls short in many realistic applications where the agents' roles may change \textit{across rounds} due to dynamic adversary, task progression, or time-varying constraints such as communication bandwidth. In this paper, we propos
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