Verifiable Retrieval for Legal Reasoning through Structure-driven Knowledge Graph
Any automation within reliability-critical contexts such as medicine or law has to be transparent and verifiable. Despite their advantages, current LLM-based systems do not meet these requirements due to their inherent black-box nature. Retrieval Augmented Generation (RAG) attempts to ground the generative process in the relevant interpretable documents, thereby reducing the risk of AI 'hallucinations' and potentially enabling verification of the initial generation context. However, as the number and size of potential sources increases, naive retrieval approaches tend to perform worse, ignoring critical context elements. In this paper we aim to tackle this problem in the context of German...
| Authors | Ibrahim Siddig, Sviatoslav Tugeev, Munir Georges |
|---|---|
| Primary category | cs.CL |
| Published | 9 October 2026 |
| Last updated at source | 13 October 2026 |
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