arXiv:2505. 02763v2 Announce Type: replace-cross Abstract: One of the central promises of legal AI is to automate drudgery -- the formal, repetitive tasks of lawyers' work that consume time without calling for much discretion.
By Matthew Dahl, Eric Mart\'inez
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...
By Theresia Veronika Rampisela, Henrik Palmer Olsen, Giovanni Colavizza
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.
By Max Prior, Niklas Wais, Matthias Grabmair
arXiv:2608. 09393v1 Announce Type: cross Abstract: We identify and quantify temporal misgrounding: the systematic retrieval and citation of the currently in-force version of a legal article when the applicable version is an earlier or future one.
By Rose Cymbler, Daniel Guez, Laurent Fabre
Legal argument mining supports passage classification, retrieval, and argument completion. This work introduces an expert-annotated dataset of 42 U.S. federal tax opinions on corporate reorganizations...
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.
By Souvick Das, Sallam Abualhaija, Domenico Bianculli