1 research outputs found
Comparative Analysis of Artificial Intelligence for Indian Legal Question Answering (AILQA) Using Different Retrieval and QA Models
Legal question-answering (QA) systems have the potential to revolutionize the
way legal professionals interact with case law documents. This paper conducts a
comparative analysis of existing artificial intelligence models for their
utility in answering legal questions within the Indian legal system,
specifically focusing on Indian Legal Question Answering (AILQA) and our study
investigates the efficacy of different retrieval and QA algorithms currently
available. Utilizing the OpenAI GPT model as a benchmark, along with query
prompts, our investigation shows that existing AILQA systems can automatically
interpret natural language queries from users and generate highly accurate
responses. This research is particularly focused on applications within the
Indian criminal justice domain, which has its own set of challenges due to its
complexity and resource constraints. In order to rigorously assess the
performance of these models, empirical evaluations are complemented by feedback
from practicing legal professionals, thereby offering a multifaceted view on
the capabilities and limitations of AI in the context of Indian legal
question-answering