Summary of Lawllm: Law Large Language Model For the Us Legal System, by Dong Shu et al.
LawLLM: Law Large Language Model for the US Legal System
by Dong Shu, Haoran Zhao, Xukun Liu, David Demeter, Mengnan Du, Yongfeng Zhang
First submitted to arxiv on: 27 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Information Retrieval (cs.IR); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces a novel multi-task model called Law Large Language Model (LawLLM) designed for the US legal domain to tackle challenges in finding relevant cases and predicting judicial outcomes. The LawLLM excels at tasks like Similar Case Retrieval, Precedent Case Recommendation, and Legal Judgment Prediction by clearly distinguishing between precedent and similar cases. To achieve this, the model employs customized data preprocessing techniques and techniques such as in-context learning (ICL) and advanced information retrieval methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The LawLLM is a machine learning tool that helps lawyers and researchers find relevant cases and predict judicial outcomes more accurately. It’s like having a super smart research assistant that can quickly find the most relevant information from a huge library of court cases! The model is very good at doing three important tasks: finding similar cases, recommending precedent cases, and predicting how judges will rule. |
Keywords
» Artificial intelligence » Large language model » Machine learning » Multi task
