Legal Question-Answering in the Indian Context: Efficacy, Challenges, and Potential of Modern AI Models

• URL: http://arxiv.org/abs/2309.14735v2
• Date: Mon, 16 Oct 2023 04:40:18 GMT
• Title: Legal Question-Answering in the Indian Context: Efficacy, Challenges, and Potential of Modern AI Models
• Authors: Shubham Kumar Nigam, Shubham Kumar Mishra, Ayush Kumar Mishra, Noel Shallum and Arnab Bhattacharya
• Abstract summary: Legal QA platforms bear the promise to metamorphose the manner in which legal experts engage with jurisprudential documents. Our discourse zeroes in on an array of retrieval and QA mechanisms, positioning the OpenAI GPT model as a reference point. The ambit of this study is tethered to the Indian criminal legal landscape, distinguished by its intricate nature and associated logistical constraints.
• Score: 3.552993426200889
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Legal QA platforms bear the promise to metamorphose the manner in which legal experts engage with jurisprudential documents. In this exposition, we embark on a comparative exploration of contemporary AI frameworks, gauging their adeptness in catering to the unique demands of the Indian legal milieu, with a keen emphasis on Indian Legal Question Answering (AILQA). Our discourse zeroes in on an array of retrieval and QA mechanisms, positioning the OpenAI GPT model as a reference point. The findings underscore the proficiency of prevailing AILQA paradigms in decoding natural language prompts and churning out precise responses. The ambit of this study is tethered to the Indian criminal legal landscape, distinguished by its intricate nature and associated logistical constraints. To ensure a holistic evaluation, we juxtapose empirical metrics with insights garnered from seasoned legal practitioners, thereby painting a comprehensive picture of AI's potential and challenges within the realm of Indian legal QA.

Related papers

• IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning [16.12863746776168]
  Legal systems worldwide are inundated with exponential growth in cases and documents. There is an imminent need to develop NLP and ML techniques for automatically processing and understanding legal documents. This paper proposes IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning.
  arXiv  Detail & Related papers  (2024-07-07T14:55:04Z)
• Unsettled Law: Time to Generate New Approaches? [1.3651236252124068]
  We identify several important and unsettled legal questions with profound ethical and societal implications arising from generative artificial intelligence (GenAI) Our key contribution is formally identifying the issues that are unique to GenAI so scholars, practitioners, and others can conduct more useful investigations and discussions. We argue that GenAI's unique attributes, including its general-purpose nature, reliance on massive datasets, and potential for both pervasive societal benefits and harms, necessitate a re-evaluation of existing legal paradigms.
  arXiv  Detail & Related papers  (2024-07-02T05:51:41Z)
• InternLM-Law: An Open Source Chinese Legal Large Language Model [72.2589401309848]
  InternLM-Law is a specialized LLM tailored for addressing diverse legal queries related to Chinese laws. We meticulously construct a dataset in the Chinese legal domain, encompassing over 1 million queries. InternLM-Law achieves the highest average performance on LawBench, outperforming state-of-the-art models, including GPT-4, on 13 out of 20 subtasks.
  arXiv  Detail & Related papers  (2024-06-21T06:19:03Z)
• Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts [6.339932924789635]
  textbfPrediction with textbfExplanation (textttPredEx) is the largest expert-annotated dataset for legal judgment prediction and explanation in the Indian context. This corpus significantly enhances the training and evaluation of AI models in legal analysis.
  arXiv  Detail & Related papers  (2024-06-06T14:57:48Z)
• Report of the 1st Workshop on Generative AI and Law [78.62063815165968]
  This report presents the takeaways of the inaugural Workshop on Generative AI and Law (GenLaw) A cross-disciplinary group of practitioners and scholars from computer science and law convened to discuss the technical, doctrinal, and policy challenges presented by law for Generative AI.
  arXiv  Detail & Related papers  (2023-11-11T04:13:37Z)
• Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models [10.834755282333589]
  Long-form Legal Question Answering dataset comprises 1,868 expert-annotated legal questions in the French language. Our experimental results demonstrate promising performance on automatic evaluation metrics. As one of the only comprehensive, expert-annotated long-form LQA dataset, LLeQA has the potential to not only accelerate research towards resolving a significant real-world issue, but also act as a rigorous benchmark for evaluating NLP models in specialized domains.
  arXiv  Detail & Related papers  (2023-09-29T08:23:19Z)
• Fairness in Agreement With European Values: An Interdisciplinary Perspective on AI Regulation [61.77881142275982]
  This interdisciplinary position paper considers various concerns surrounding fairness and discrimination in AI, and discusses how AI regulations address them. We first look at AI and fairness through the lenses of law, (AI) industry, sociotechnology, and (moral) philosophy, and present various perspectives. We identify and propose the roles AI Regulation should take to make the endeavor of the AI Act a success in terms of AI fairness concerns.
  arXiv  Detail & Related papers  (2022-06-08T12:32:08Z)
• An Uncommon Task: Participatory Design in Legal AI [64.54460979588075]
  We examine a notable yet understudied AI design process in the legal domain that took place over a decade ago. We show how an interactive simulation methodology allowed computer scientists and lawyers to become co-designers.
  arXiv  Detail & Related papers  (2022-03-08T15:46:52Z)
• Indian Legal NLP Benchmarks : A Survey [0.0]
  There is a need to create separate Natural Language Processing benchmarks for Indian Legal Text. This will spur innovation in applications of Natural language Processing for Indian Legal Text.
  arXiv  Detail & Related papers  (2021-07-13T13:10:10Z)
• Lawformer: A Pre-trained Language Model for Chinese Legal Long Documents [56.40163943394202]
  We release the Longformer-based pre-trained language model, named as Lawformer, for Chinese legal long documents understanding. We evaluate Lawformer on a variety of LegalAI tasks, including judgment prediction, similar case retrieval, legal reading comprehension, and legal question answering.
  arXiv  Detail & Related papers  (2021-05-09T09:39:25Z)
• How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence [81.04070052740596]
  Legal Artificial Intelligence (LegalAI) focuses on applying the technology of artificial intelligence, especially natural language processing, to benefit tasks in the legal domain. This paper introduces the history, the current state, and the future directions of research in LegalAI.
  arXiv  Detail & Related papers  (2020-04-25T14:45:15Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.