DTKG: Dual-Track Knowledge Graph-Verified Reasoning Framework for Multi-Hop QA

• URL: http://arxiv.org/abs/2510.16302v1
• Date: Sat, 18 Oct 2025 02:19:11 GMT
• Title: DTKG: Dual-Track Knowledge Graph-Verified Reasoning Framework for Multi-Hop QA
• Authors: Changhao Wang, Yanfang Liu, Xinxin Fan, Anzhi Zhou, Lao Tian, Yunfeng Lu,
• Abstract summary: Multi-hop reasoning for question answering plays a critical role in retrieval-augmented generation.<n>We propose a novel dual-track KG verification and reasoning framework DTKG.
• Score: 8.598540768292809
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Multi-hop reasoning for question answering (QA) plays a critical role in retrieval-augmented generation (RAG) for modern large language models (LLMs). The accurate answer can be obtained through retrieving relational structure of entities from knowledge graph (KG). Regarding the inherent relation-dependency and reasoning pattern, multi-hop reasoning can be in general classified into two categories: i) parallel fact-verification multi-hop reasoning question, i.e., requiring simultaneous verifications of multiple independent sub-questions; and ii) chained multi-hop reasoning questions, i.e., demanding sequential multi-step inference with intermediate conclusions serving as essential premises for subsequent reasoning. Currently, the multi-hop reasoning approaches singly employ one of two techniques: LLM response-based fact verification and KG path-based chain construction. Nevertheless, the former excels at parallel fact-verification but underperforms on chained reasoning tasks, while the latter demonstrates proficiency in chained multi-hop reasoning but suffers from redundant path retrieval when handling parallel fact-verification reasoning. These limitations deteriorate the efficiency and accuracy for multi-hop QA tasks. To address this challenge, we propose a novel dual-track KG verification and reasoning framework DTKG, which is inspired by the Dual Process Theory in cognitive science. Specifically, DTKG comprises two main stages: the Classification Stage and the Branch Processing Stage.

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