[2504.03486] Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej

Computer Science > Computation and Language arXiv:2504.03486 (cs) [Submitted on 4 Apr 2025 (v1), last revised 25 Mar 2026 (this version, v2)] Title:Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej Authors:Shubham Kumar Nigam, Balaramamahanthi Deepak Patnaik, Noel Shallum, Kripabandhu Ghosh, Arnab Bhattacharya View a PDF of the paper titled Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej, by Shubham Kumar Nigam and 4 other authors View PDF Abstract:Automating legal document drafting can improve efficiency and reduce the burden of manual legal work. Yet, the structured generation of private legal documents remains underexplored, particularly in the Indian context, due to the scarcity of public datasets and the complexity of adapting models for long-form legal drafting. To address this gap, we introduce VidhikDastaavej, a large-scale, anonymized dataset of private legal documents curated in collaboration with an Indian law firm. Covering 133 diverse categories, this dataset is the first resource of its kind and provides a foundation for research in structured legal text generation and Legal AI more broadly. We further propose a Model-Agnostic Wrapper (MAW), a two-stage generation framework that first plans the section structure of a legal draft and then generates each section with retrieval-based prompts. MAW is independent of any specific LLM, making it adaptable across...