{
  "id": 13013,
  "url": "https://arxiv.org/abs/2607.20734",
  "title": "LLMs Get Lost in Evolving User Intent",
  "summary": "As LLMs become more capable, they are increasingly deployed as collaborative agents, taking on user-delegated tasks through iterative interaction. Yet genuine interaction is inherently dynamic: users rarely specify their intent upfront, instead disclosing, revising, and reshaping it as the conversation unfolds. Despite this, LLMs are still predominantly evaluated or trained in single-turn, fully-specified settings, leaving open a fundamental question: how well do LLMs track and act on user inten",
  "authors": "Jihoon Tack, Philippe Laban, Jennifer Neville",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-21T20:00:00.000Z",
  "fetched_at": "2026-07-25T05:10:48.796Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/13013",
  "original_url": "https://arxiv.org/abs/2607.20734",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}