AI RESEARCH
G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge
arXiv CS.AI
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ArXi:2509.24276v4 Announce Type: replace Large language models (LLMs) excel at complex reasoning but remain limited by static and incomplete parametric knowledge. Retrieval-augmented generation (RAG) mitigates this by incorporating external knowledge, yet existing RAGs struggle with knowledge-intensive tasks due to fragmented information and weak modeling of knowledge structure. Graphs offer a natural way to model relationships within knowledge, but LLMs are inherently unstructured and cannot effectively reason over graph-structured data.