{
  "id": 17359,
  "url": "https://arxiv.org/abs/2608.06068v1",
  "title": "Cleo: A Transparent and Controllable Chatbot for Conversational Commerce",
  "summary": "We demonstrate Cleo, a transparent and controllable conversational product advisor that addresses the challenges of opacity, unpredictability of LLMs, and the complexity of comparisons in conversational commerce. With our chatbot system, we make four contributions: First, we introduce transparency by prompting the LLM to reflect on interpreted user needs, while an auditable ranking mechanism reveals loss values per attribute, explaining ranking decisions. Second, we propose controllability throu",
  "authors": "Kevin Schott, Jan Lattenkamp, Daniel Hienert, Dagmar Kern",
  "category": "research",
  "topics": "transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-06T14:12:14.000Z",
  "fetched_at": "2026-08-07T05:10:58.501Z",
  "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/17359",
  "original_url": "https://arxiv.org/abs/2608.06068v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}