<ul><li>Developing advanced reasoning capabilities in Large Language Models (LLMs) is a challenge.</li><li>Process Reward Models (PRMs) show promise in enhancing reasoning, particularly in mathematical reasoning.</li><li>In this work, GraphSILO dataset is introduced for graph reasoning problems with step-wise labels.</li><li>Experimental results show that GraphPRM significantly improves LLM performance in graph reasoning tasks and other domains.</li></ul>

Rewarding Graph Reasoning Process makes LLMs more Generalized Reasoners

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