{
  "id": 17763,
  "url": "https://arxiv.org/abs/2608.06955",
  "title": "Critical Acclaim Orientation in Large Language Models: Evidence from Film Preference Elicitation",
  "summary": "arXiv:2608.06955v1 Announce Type: cross Abstract: Large language models (LLMs) are trained on corpora that contain expressions of human judgment about films, books, music, and more. Yet whether LLMs systematically reproduce evaluative hierarchies remains unclear. Prior research on cultural bias in LLMs suggests competing expectations: models may mirror the popularity signals of internet texts, or may reproduce forms of prestige embedded in critical discourse. We probe this question through a stu",
  "authors": "Jonghyun Jee, Aaron Shaw",
  "category": "research",
  "topics": "bias-fairness",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-10T04:00:00.000Z",
  "fetched_at": "2026-08-10T05:10:00.488Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/17763",
  "original_url": "https://arxiv.org/abs/2608.06955",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}