Brain-Inspired Graph Multi-Agent Systems for LLM Reasoning

ArXi:2603.15371v1 Announce Type: new Large Language Models (LLMs) have nstrated remarkable capabilities across a wide range of language tasks, yet complex multi-step reasoning remains a fundamental challenge. While Large Reasoning Models (LRMs) equipped with extended chain-of-thought mechanisms nstrate improved performance over standard LLMs, both model types still suffer from accuracy collapse on sufficiently complex tasks, suggesting that scaling model-level reasoning alone is insufficient.