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LLM adapted for Indian law achieves 60% on bar exam, beats GPT-3.5

Researchers have developed a framework called Legal Assist AI to address the gap in legal assistance access in India. This system utilizes a smaller, 8-billion-parameter quantized Llama 3.1 model, enhanced with a Retrieval-Augmented Generation (RAG) system and prompt engineering. The framework integrates over 600 legal documents, including recent legislation like the Bharatiya Nyaya Sanhita, and successfully mitigates hallucinations. It achieved a score of 60.08% on the All-India Bar Examination benchmark, outperforming GPT-3.5 Turbo, and demonstrated 22 times greater parameter efficiency. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Demonstrates a cost-effective approach to building specialized legal AI tools, potentially improving access to justice.

RANK_REASON This is a research paper detailing a novel framework and benchmark results for domain-specific LLM adaptation.

Read on arXiv cs.CL →

COVERAGE [1]

  1. arXiv cs.CL TIER_1 · Jatin Gupta, Akhil Sharma, Saransh Singhania, Ali Imam Abidi ·

    Lightweight Domain Adaptation of a Large Language Model for Legal Assistance in the Indian Context

    arXiv:2505.22003v2 Announce Type: replace Abstract: In India, access to legal assistance for the general public has been observed to have a critical gap, as many citizens are not able to take full advantage of their legal rights due to limited access and awareness of apposite leg…