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DeliLaw: A Chinese Legal Counselling System Based on a Large Language Model

arXiv 2408.00357 ↗First posted 1 Aug 2024cs.CLcited by 1

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Abstract (arXiv)

Traditional legal retrieval systems designed to retrieve legal documents, statutes, precedents, and other legal information are unable to give satisfactory answers due to lack of semantic understanding of specific questions. Large Language Models (LLMs) have achieved excellent results in a variety of natural language processing tasks, which inspired us that we train a LLM in the legal domain to help legal retrieval. However, in the Chinese legal domain, due to the complexity of legal questions and the rigour of legal articles, there is no legal large model with satisfactory practical application yet. In this paper, we present DeliLaw, a Chinese legal counselling system based on a large language model. DeliLaw integrates a legal retrieval module and a case retrieval module to overcome the model hallucination. Users can consult professional legal questions, search for legal articles and relevant judgement cases, etc. on the DeliLaw system in a dialogue mode. In addition, DeliLaw supports the use of English for counseling. we provide the address of the system: https://data.delilegal.com/lawQuestion.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 7 of its 16 references that are in the map. First posted on arXiv 1 Aug 2024.

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References · 7

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  2. 2023WizardLM: Empowering large pre-trained language models to follow complex instructionscited by 1,116
  3. 2023LIMA: Less Is More for Alignmentcited by 1,080
  4. 2021GLM: General Language Model Pretraining with Autoregressive Blank Infillingcited by 1,026
  5. 2022Promptagator: Few-shot Dense Retrieval From 8 Examplescited by 233
  6. 2023HuatuoGPT, towards Taming Language Model to Be a Doctorcited by 211
  7. 2023UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankerscited by 37

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