DarkForest: Less Talk, Higher Accuracy for Multi-Agent LLMs 事件

DarkForest: Less Talk, Higher Accuracy for Multi-Agent LLMs arXiv:2605.25188v1 Announce Type: new Abstract: Multi-agent LLM systems improve reasoning by combining outputs from multiple agents, but interaction-heavy methods can introduce error propagation and high communication overhead. When agents exchange raw responses or reasoning traces, incorrect intermediate reasoning may be adopted and amplified, leading to confident but wrong consensus; multi-round communication also increases token con