most citedCan Graph Learning Improve Planning in LLM-based Agents?

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cs.CL2025

From Sequence to Structure: Uncovering Substructure Reasoning in Transformers

Xinnan Dai, Kai Yang, Jay Revolinsky +4

Recent studies suggest that large language models (LLMs) possess the capability to solve graph reasoning tasks. Notably, even when graph structures are embedded within textual desc…