1 citations · 2 across the 6 of their papers we have counts for
7 papers · 1 filter
ReGal: A First Look at PPO-based Legal AI for Judgment Prediction and Summarization in India
Shubham Kumar Nigam, Tanuj Tyagi, Siddharth Shukla +6
This paper presents an early exploration of reinforcement learning methodologies for legal AI in the Indian context. We introduce Reinforcement Learning-based Legal Reasoning (ReGa…
IBPS: Indian Bail Prediction System
Puspesh Kumar Srivastava, Uddeshya Raj, Praveen Patel +3
Bail decisions are among the most frequently adjudicated matters in Indian courts, yet they remain plagued by subjectivity, delays, and inconsistencies. With over 75% of India's pr…
NyayaRAG: Realistic Legal Judgment Prediction with RAG under the Indian Common Law System
Shubham Kumar Nigam, Balaramamahanthi Deepak Patnaik, Shivam Mishra +4
Legal Judgment Prediction (LJP) has emerged as a key area in AI for law, aiming to automate judicial outcome forecasting and enhance interpretability in legal reasoning. While prev…
Segment First, Retrieve Better: Realistic Legal Search via Rhetorical Role-Based Queries
Shubham Kumar Nigam, Tanmay Dubey, Noel Shallum +1
Legal precedent retrieval is a cornerstone of the common law system, governed by the principle of stare decisis, which demands consistency in judicial decisions. However, the growi…
TathyaNyaya and FactLegalLlama: Advancing Factual Judgment Prediction and Explanation in the Indian Legal Context
Shubham Kumar Nigam, Balaramamahanthi Deepak Patnaik, Shivam Mishra +3
In the landscape of Fact-based Judgment Prediction and Explanation (FJPE), reliance on factual data is essential for developing robust and realistic AI-driven decision-making tools…
LegalSeg: Unlocking the Structure of Indian Legal Judgments Through Rhetorical Role Classification
Shubham Kumar Nigam, Tanmay Dubey, Govind Sharma +3
In this paper, we address the task of semantic segmentation of legal documents through rhetorical role classification, with a focus on Indian legal judgments. We introduce LegalSeg…