AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent 事件

AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent arXiv:2602.03955v3 Announce Type: replace Abstract: While large language model (LLM) multi-agent systems achieve superior reasoning performance through iterative debate, practical deployment is limited by their high computational cost and error propagation. This paper proposes AgentArk, a novel framework to distill multi-agent dynamics into the weights of a single model, effectively transforming explicit test-time interaction