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The Path Matters: Evaluating Small Language Models Beyond Answer Accuracy in KGQA
Small language models (SLMs) are increasingly paired with knowledge graphs (KGs), yet end-to-end KG question answering conflates graph access, search, navigation, reasoning, and answer generation. This coupling makes it difficult both to determine whether an SLM can faithfully execute the reasoning path implied by a question and to attribute failures to navigation rather than to other stages of the pipeline. We isolate this capability by employing the THESEUS navigation and traceability framework and using frozen, off-the-shelf SLMs as local action policies. At each hop, the environment expose
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-23T10:38:23.000Z
First collected: 2026-09-24T01:22:21.678Z. This is not the publication date.