Evaluating RAG for French immigration law: a benchmark and baseline study2607.24449AuthorsAnnia Abtout,Julien Delaunay,Monika Ewa RakoczyAbstractInternational recruitment in France requires navigating a layered legal framework absent from existing legal AI benchmarks. We present a publicly available benchmark and first comparative evaluation for this domain, covering permit-type recommendation, required-document retrieval, and legal citation coverage. Comparing a parametric LLM baseline against dense retrieval augmentation at two model scales (Qwen3.5-9B and -27B) on 52 annotated synthetic profiles, we find that retrieval improves administrative guidance at both scales, most notably permit-type accuracy. Our results confirm that retrieval grounding is important for more reliable administrative guidance in this domain, and motivate further investigation of hybrid retrieval strategies.ResourcesView on Hugging FaceRead PDFArXiv
Evaluating RAG for French immigration law: a benchmark and baseline study
International recruitment in France requires navigating a layered legal framework absent from existing legal AI benchmarks. We present a publicly available b...
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