{
  "id": 18277,
  "url": "https://arxiv.org/abs/2608.09294v1",
  "title": "Graphing the Everyday: A Neurosymbolic Approach to Eliciting Routines for Just-In-Time Adaptive Interventions",
  "summary": "Just-In-Time Adaptive Interventions (JITAIs) increasingly rely on conversational agents to elicit user routines, yet translating fluid human dialogue into rigid schedule data remains a significant challenge. We conducted a qualitative investigation of a neurosymbolic pipeline, combining Large Language Models (LLMs) with a Neo4j knowledge graph, to map unstructured verbal narratives into actionable interventions. Through human-centric evaluation using natural-language playbacks, we identified a c",
  "authors": "Shakyani Jayasiriwardene, Blake Mountford, Meican Ma, Niels van Berkel, Nicholas Koemel, Matthew Ahmadi, Jorge Goncalves, Emmanuel Stamatakis, Zhanna Sarsenbayeva",
  "category": "research",
  "topics": "agents-autonomy,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-10T08:45:54.000Z",
  "fetched_at": "2026-08-11T05:10:37.351Z",
  "source_slug": "x-arxiv-cs-hc",
  "source_name": "arXiv cs.HC",
  "source_homepage": "https://arxiv.org/list/cs.HC/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/18277",
  "original_url": "https://arxiv.org/abs/2608.09294v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}