{
  "id": 18072,
  "url": "https://link.springer.com/article/10.1007/s10506-026-09534-5",
  "title": "Explainable Statute Prediction via Attention-based Model and LLM Prompting",
  "summary": "In this paper, we explore the problem of automatic statute prediction where for a given case description, a subset of relevant statutes are to be predicted. Here, the term statute refers to a section, a sub-section, or an article of any specific Act. Addressing this problem would be useful in several applications such as AI-assistant for lawyers and legal question answering system. For better user acceptance of such Legal AI systems, we believe the predictions should also be accompanied by human",
  "authors": null,
  "category": "research",
  "topics": "transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-10T00:00:00.000Z",
  "fetched_at": "2026-08-11T05:10:37.351Z",
  "source_slug": "x-artificial-intelligence-and-law",
  "source_name": "Artificial Intelligence and Law",
  "source_homepage": "https://link.springer.com/journal/10506",
  "ethics_ai_record_url": "https://ethics.ai/record/18072",
  "original_url": "https://link.springer.com/article/10.1007/s10506-026-09534-5",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}