Foresight-over-Graph: Reasoning Beyond Local Horizons for Knowledge Base Question Answering
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Computer Science > Computation and Language
arXiv:2610.08388 (cs)
[Submitted on 6 Oct 2026]
Title:Foresight-over-Graph: Reasoning Beyond Local Horizons for Knowledge Base Question Answering
View a PDF of the paper titled Foresight-over-Graph: Reasoning Beyond Local Horizons for Knowledge Base Question Answering, by Yang Hong and 4 other authors
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Abstract:Large language models (LLMs) have demonstrated strong capabilities in question answering, yet they still frequently suffer from hallucinations on knowledge-intensive tasks. Knowledge graphs (KGs) provide LLMs with structured, interpretable, and updatable factual grounding, making them a promising external knowledge source for reliable reasoning. However, existing LLM-guided graph reasoning methods typically rely on hop-wise greedy or beam-style pruning during evidence retrieval. Such local decision processes are inherently myopic: evidence that appears weak near the source may become crucial only after deeper graph context is explored, causing answer-critical branches to be discarded prematurely and making the reasoning chain difficult to recover. To address this limitation, we propose Foresight-over-Graph (FoG), a foresight-aware evidence retrieval framework for knowledge base question answering (KBQA). FoG iteratively constructs a question-relevant evidence subgraph and uses far-to-near feedback to guide path exploration, and maintains a compact memory subgraph to support continued exploration. Extensive experiments on widely used KBQA benchmarks demonstrate that FoG achieves state-of-the-art performance, with a particularly large improvement of 16.58% in Hit on CWQ, while also reducing LLM calls and token usage. Our code is available at this https URL .
| Comments: | 25 pages, 10 figures. Accepted at NeurIPS 2026 |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.08388 [cs.CL] |
| (or arXiv:2610.08388v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.08388
arXiv-issued DOI via DataCite (pending registration)
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View a PDF of the paper titled Foresight-over-Graph: Reasoning Beyond Local Horizons for Knowledge Base Question Answering, by Yang Hong and 4 other authors
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