NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering
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Computer Science > Computation and Language
arXiv:2602.15353 (cs)
[Submitted on 17 Feb 2026 (v1), last revised 22 Jul 2026 (this version, v3)]
Title:NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering
Authors:Rong Fu, Yang Li, Zeyu Zhang, Jiekai Wu, Yaohua Liu, Shuaishuai Cao, Yangchen Zeng, Yuhang Zhang, Xiaojing Du, Simon Fong
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Abstract:Large pretrained language models and neural reasoning systems have advanced many natural language tasks, yet they remain challenged by knowledge-intensive queries that require precise, structured multi-hop inference. Knowledge graphs provide a compact symbolic substrate for factual grounding, but integrating graph structure with neural models is nontrivial: naively embedding graph facts into prompts leads to inefficiency and fragility, while purely symbolic or search-heavy approaches can be costly in retrievals and lack gradient-based refinement. We introduce NeuroSymActive, a modular framework that combines a differentiable neural-symbolic reasoning layer with an active, value-guided exploration controller for Knowledge Graph Question Answering. The method couples soft-unification style symbolic modules with a neural path evaluator and a Monte-Carlo style exploration policy that prioritizes high-value path expansions. Empirical results on standard KGQA benchmarks show that NeuroSymActive attains strong answer accuracy while reducing the number of expensive graph lookups and model calls compared to common retrieval-augmented baselines.
| Comments: | 26 pages, 7 figures. In the previous version, Juntendo University was erroneously listed as the affiliation; we must clarify that this paper has absolutely no relation to Juntendo University. Therefore, we have replaced this affiliation in the new version |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2602.15353 [cs.CL] |
| (or arXiv:2602.15353v3 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2602.15353
arXiv-issued DOI via DataCite
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Submission history
From: Rong Fu [view email][v1] Tue, 17 Feb 2026 04:47:29 UTC (3,301 KB)
[v2] Wed, 22 Apr 2026 08:50:15 UTC (879 KB)
[v3] Wed, 22 Jul 2026 04:49:25 UTC (879 KB)
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View a PDF of the paper titled NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering, by Rong Fu and 9 other authors
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