{
  "id": 5869,
  "url": "https://arxiv.org/abs/2604.14223v1",
  "title": "TRACE: A Conversational Framework for Sustainable Tourism Recommendation with Agentic Counterfactual Explanations",
  "summary": "Traditional conversational travel recommender systems primarily optimize for user relevance and convenience, often reinforcing popular, overcrowded destinations and carbon-intensive travel choices. To address this, we present TRACE (Tourism Recommendation with Agentic Counterfactual Explanations), a multi-agent, LLM-based framework that promotes sustainable tourism through interactive nudging. TRACE uses a modular orchestrator-worker architecture where specialized agents elicit latent sustainabi",
  "authors": "Ashmi Banerjee, Adithi Satish, Wolfgang Wörndl, Yashar Deldjoo",
  "category": "research",
  "topics": "agents-autonomy,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-14T12:35:21.000Z",
  "fetched_at": "2026-07-14T16:32:06.466Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5869",
  "original_url": "https://arxiv.org/abs/2604.14223v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}