Nyay-Darpan: Enhancing Decision Making Through Summarization and Case Retrieval for Consumer Law in India
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866916886231384064 |
|---|---|
| author | Bhattacharyya, Swapnil Kashid, Harshvivek Ganatra, Shrey Anaokar, Spandan Nair, Shruti Sekhar, Reshma Manohar, Siddharth Hemrajani, Rahul Bhattacharyya, Pushpak |
| author_facet | Bhattacharyya, Swapnil Kashid, Harshvivek Ganatra, Shrey Anaokar, Spandan Nair, Shruti Sekhar, Reshma Manohar, Siddharth Hemrajani, Rahul Bhattacharyya, Pushpak |
| contents | AI-based judicial assistance and case prediction have been extensively studied in criminal and civil domains, but remain largely unexplored in consumer law, especially in India. In this paper, we present Nyay-Darpan, a novel two-in-one framework that (i) summarizes consumer case files and (ii) retrieves similar case judgements to aid decision-making in consumer dispute resolution. Our methodology not only addresses the gap in consumer law AI tools but also introduces an innovative approach to evaluate the quality of the summary. The term 'Nyay-Darpan' translates into 'Mirror of Justice', symbolizing the ability of our tool to reflect the core of consumer disputes through precise summarization and intelligent case retrieval. Our system achieves over 75 percent accuracy in similar case prediction and approximately 70 percent accuracy across material summary evaluation metrics, demonstrating its practical effectiveness. We will publicly release the Nyay-Darpan framework and dataset to promote reproducibility and facilitate further research in this underexplored yet impactful domain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_06090 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Nyay-Darpan: Enhancing Decision Making Through Summarization and Case Retrieval for Consumer Law in India Bhattacharyya, Swapnil Kashid, Harshvivek Ganatra, Shrey Anaokar, Spandan Nair, Shruti Sekhar, Reshma Manohar, Siddharth Hemrajani, Rahul Bhattacharyya, Pushpak Information Retrieval Computation and Language AI-based judicial assistance and case prediction have been extensively studied in criminal and civil domains, but remain largely unexplored in consumer law, especially in India. In this paper, we present Nyay-Darpan, a novel two-in-one framework that (i) summarizes consumer case files and (ii) retrieves similar case judgements to aid decision-making in consumer dispute resolution. Our methodology not only addresses the gap in consumer law AI tools but also introduces an innovative approach to evaluate the quality of the summary. The term 'Nyay-Darpan' translates into 'Mirror of Justice', symbolizing the ability of our tool to reflect the core of consumer disputes through precise summarization and intelligent case retrieval. Our system achieves over 75 percent accuracy in similar case prediction and approximately 70 percent accuracy across material summary evaluation metrics, demonstrating its practical effectiveness. We will publicly release the Nyay-Darpan framework and dataset to promote reproducibility and facilitate further research in this underexplored yet impactful domain. |
| title | Nyay-Darpan: Enhancing Decision Making Through Summarization and Case Retrieval for Consumer Law in India |
| topic | Information Retrieval Computation and Language |
| url | https://arxiv.org/abs/2507.06090 |