@inproceedings{bhattacharyya-etal-2025-nyay,
    title = "Nyay-Darpan: Enhancing Decision Making Through Summarization and Case Retrieval for Consumer Law in {I}ndia",
    author = "Bhattacharyya, Swapnil  and
      Kashid, Harshvivek  and
      Ganatra, Shrey  and
      Anaokar, Spandan  and
      Sekhar, Reshma  and
      Nair, Shruthi N  and
      Manohar, Siddharth  and
      Hemrajani, Rahul  and
      Bhattacharyya, Pushpak",
    editor = "Modi, Ashutosh  and
      Ghosh, Saptarshi  and
      Ekbal, Asif  and
      Goyal, Pawan  and
      Jain, Sarika  and
      Joshi, Abhinav  and
      Mishra, Shivani  and
      Datta, Debtanu  and
      Paul, Shounak  and
      Singh, Kshetrimayum Boynao  and
      Kumar, Sandeep",
    booktitle = "Proceedings of the 1st Workshop on NLP for Empowering Justice (JUST-NLP 2025)",
    month = dec,
    year = "2025",
    address = "Mumbai, India",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.justnlp-main.8/",
    pages = "73--100",
    ISBN = "979-8-89176-312-8",
    abstract = "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 precision 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."
}