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Harald Sack

Interesting new paper: "Graph-constrained Reasoning (GCR)" - Enabling Faithful KG-grounded LLM Reasoning with Zero Hallucination! 🧠 by Linhao Luo, Zicheng Zhao, Chen Gong, Gholamreza Haffari, Shirui Pan

paper: arxiv.org/pdf/2410.13080
GCR code on GitHub: github.com/RManLuo/graph-const

Illustration of existing KG-enhanced LLM reasoning paradigms and proposed graphconstrained reasoning (GCR). 1) First, given a KG, we convert it into the KG-Trie, serving as a structured index to facilitate efficient reasoning path searches using LLMs. 2) Then, we design a graph-constrained decoding process that employs a lightweight KG-specialized LLM to generate multiple KG-grounded reasoning paths and hypothesis answers. This ensures the faithfulness of the reasoning process while leveraging the strong capabilities of LLMs to efficiently explore reasoning paths within KGs. 3) Finally, we input the generated reasoning paths and hypothesis answers into a powerful general LLM to utilize its inductive reasoning ability to produce final answers.
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