arXiv (All)
open access
Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval
Statutory corpora and judicial decisions are growing faster than legal professionals can read them, while individual judgments often exceed the context limits of standard encoder models. Transformer architectures dominate legal NLP benchmarks, but their quadratic attention complexity can require tru
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- LawCompass: Navigating from Legal QA to Multi-Agent Deep Research with Grounded Evidence#1155962
- LexCLiPR: Cross-Lingual Paragraph Retrieval from Legal Judgments#1178507
- SoK: Grading Open-Text Legal Answers, from Law School Exams to Trustworthy Rubric Judges#1354673
- Legal Information Retrieval and Entailment Using Transformer-based Approaches#679120
- Using Citation Analysis Techniques for Computer-Assisted Legal Research in Continental Jurisdictions#679181
Record · ID 1233714
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive