Do Latent Channels Actually Communicate? A Causal Audit of Latent Multi-Agent LLM· 大模型多代理系统中的潜在通信
Latent communication in large language model (LLM)-based multi-agent systems (MAS) transmits continuous internal representations instead of text, but greater representational capacity does not establish that the receiver uses task-relevant information. End-task performance alone also cannot reveal whether an observed effect depends on message presence, content generated for the evaluated example, or information supplied by a separate agent. We introduce a causal audit that applies controlled message replacements at the boundary where the sender-produced representation enters the receiver. Four message settings support five measurements of encoded sender information, receiver sensitivity to message presence and identity, the task value of example-specific content, and the additional value s
研究大模型多代理系统中潜在通信的有效性和因果关系
- 核心方法
- 通过引入因果审计方法,控制消息替换,评估接收者对消息存在和内容的敏感性
- 适合谁读
- 研究者、工程师
- 要解决的问题
- 探讨多代理系统中的潜在通信是否真正传递了任务相关的信息
- 关键实验
- 设计了四种消息设置,进行了五项关键测量
- 主要贡献
- 提出了一种新的因果审计方法,用于更精确地测量多代理系统中潜在通信的效果
- 意义与局限
- 研究揭示了潜在通信在多代理系统中的实际作用,为未来的设计和优化提供了依据。但方法主要针对特定任务,可能需要进一步扩展。