# Evaluating AI for Law: Bridging the Gap with Open-Source Solutions

Source: [Evaluating AI for Law: Bridging the Gap with Open-Source Solutions](<https://www.sota2.com/research/paper/68fa72ed1e209131cea59481>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T02:37:39.153Z

Authors: Rohan Bhambhoria, Samuel Dahan, Jonathan Li, Xiaodan Zhu

Published: 2024-04-18T17:26:01.000Z

## Abstract

This study evaluates the performance of general-purpose AI, like ChatGPT, in legal question-answering tasks, highlighting significant risks to legal professionals and clients. It suggests leveraging foundational models enhanced by domain-specific knowledge to overcome these issues. The paper advocates for creating open-source legal AI systems to improve accuracy, transparency, and narrative diversity, addressing general AI's shortcomings in legal contexts.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2404.12349>)

[PDF](<https://arxiv.org/pdf/2404.12349.pdf>)