mlsanityData to 7 Oct 2026

LexDrafter: Terminology Drafting for Legislative Documents using Retrieval Augmented Generation

arXiv 2403.16295 ↗First posted 24 Mar 2024cs.CLcited by 6

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Abstract (arXiv)

With the increase in legislative documents at the EU, the number of new terms and their definitions is increasing as well. As per the Joint Practical Guide of the European Parliament, the Council and the Commission, terms used in legal documents shall be consistent, and identical concepts shall be expressed without departing from their meaning in ordinary, legal, or technical language. Thus, while drafting a new legislative document, having a framework that provides insights about existing definitions and helps define new terms based on a document's context will support such harmonized legal definitions across different regulations and thus avoid ambiguities. In this paper, we present LexDrafter, a framework that assists in drafting Definitions articles for legislative documents using retrieval augmented generation (RAG) and existing term definitions present in different legislative documents. For this, definition elements are built by extracting definitions from existing documents. Using definition elements and RAG, a Definitions article can be suggested on demand for a legislative document that is being drafted. We demonstrate and evaluate the functionality of LexDrafter using a collection of EU documents from the energy domain. The code for LexDrafter framework is available at https://github.com/achouhan93/LexDrafter.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 13 of its 33 references that are in the map. First posted on arXiv 24 Mar 2024.

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13 of 33 references.

References · 13

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  4. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  5. 2020BLEURT: Learning Robust Metrics for Text Generationcited by 1,196
  6. 2020Evaluation of Text Generation: A Surveycited by 275
  7. 2022EUR-Lex-Sum: A Multi- and Cross-lingual Dataset for Long-form Summarization in the Legal Domaincited by 39
  8. 2023Natural Language Processing in the Legal Domaincited by 38
  9. 2019Extreme Multi-Label Legal Text Classification: A case study in EU Legislationcited by 26
  10. 2023FABULA: Intelligence Report Generation Using Retrieval-Augmented Narrative Constructioncited by 10
  11. 2024From RAGs to riches: Utilizing large language models to write documents for clinical trialscited by 6
  12. 2021CLAUSEREC: A Clause Recommendation Framework for AI-aided Contract Authoringcited by 4
1 more
  1. 2021Document Automation Architectures and Technologies: A Surveycited by 3

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Citing papers per year: 2024: 1; 2025: 5.

6 papers.

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  1. 2025ASVRI-Legal: Fine-Tuning LLMs with Retrieval Augmented Generation for Enhanced Legal Regulation
  2. 2024LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain
  3. 2026LegalCheck: Retrieval- and Context-Augmented Generation for Drafting Municipal Legal Advice Letters
  4. 2025All for law and law for all: Adaptive RAG Pipeline for Legal Research
  5. 2025Towards Reliable Retrieval in RAG Systems for Large Legal Datasets
  6. 2025Poly-Vector Retrieval: Reference and Content Embeddings for Legal Documents
  7. 2026Legal-DC: Benchmarking Retrieval-Augmented Generation for Legal Documents
  8. 2026Chunking German Legal Code