The Flow has not summarised this story yet — read it at arXiv Computation and Language.
arXiv:2608.03756v2 Announce Type: cross Abstract: A common task in legal Information Retrieval (IR) is to find relevant legal sources from case-law collections. While legal practice often requires pi...
Statute retrieval is a fundamental task in legal information retrieval, yet existing approaches struggle to bridge the gap between colloquial legal queries and formal statutory language. In this paper, we propose GCSR, a generative statute retrieval framework that reformulates statute retrieval as a sequence generation problem and internalizes statutory knowledge into a generative model.
arXiv:2609.14739v1 Announce Type: cross Abstract: Large language models are increasingly used in high-stakes domains such as law, where systems must ground their reasoning in retrieved evidence and a...
arXiv:2605. 21071v4 Announce Type: replace-cross Abstract: The rapid progress of large language models (LLMs) is shifting semantic search toward a question-answering paradigm, where users ask questions and LLMs generate responses.
arXiv:2608. 18752v2 Announce Type: replace-cross Abstract: Statutory retrieval is necessary for citation-grounded legal question answering, but remains underexplored for Greek.
The paper introduces an automated pipeline that converts court decisions into legal commentaries for specific German Civil Code sections, using paragraph extraction, summarization, keyword clustering, and large language models to generate headings and citation-rich sections. The system processes 4,555 decisions from the German Federal Court of Justice, evaluates the output on relevance, heading match, citation faithfulness, cluster distinction, and logical ordering, and demonstrates that rapid, low-cost commentary generation is feasible while noting limitations due to source restrictions and legal reasoning norms.