1 citations · 1 across the 4 of their papers we have counts for
11 papers · 1 filter
AILQA: Evaluating AI-Driven Legal Question Answering Systems for the Indian Legal System
Shubham Kumar Nigam, Shubham Kumar Mishra, Noel Shallum +2
This comprehensive study introduces an advanced Artificial Intelligence for Indian Legal Question Answering (AILQA) system tailored to the Indian legal context. AILQA leverages a v…
NyayaMind- A Framework for Transparent Legal Reasoning and Judgment Prediction in the Indian Legal System
Parjanya Aditya Shukla, Shubham Kumar Nigam, Debtanu Datta +5
Court Judgment Prediction and Explanation (CJPE) aims to predict a judicial decision and provide a legally grounded explanation for a given case based on the facts, legal issues, a…
Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej
Shubham Kumar Nigam, Balaramamahanthi Deepak Patnaik, Noel Shallum +2
Automating legal document drafting can improve efficiency and reduce the burden of manual legal work. Yet, the structured generation of private legal documents remains underexplore…
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…
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…
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…