{
  "id": 3184,
  "url": "https://arxiv.org/abs/2606.04274v1",
  "title": "Long Live Fine-Tuning: Task-Specific Transformers Outperform Zero-Shot LLMs for Misinformation Response Classification on Reddit",
  "summary": "As large language models (LLMs) become default tools for online information verification, an implicit assumption follows them: that scale and general capability are sufficient for nuanced classification of misinformation discourse. We test this assumption directly on 900 Reddit comments spanning three PolitiFact-verified misinformation claims (environment, health, immigration), labelled as belief (propagates the claim), fact-check (corrects it), or other. We compare nine models across three para",
  "authors": "JooYoung Lee, Lin Tian, Angela Brillantes, Adriana-Simona Mihăiţă, Marian-Andrei Rizoiu",
  "category": "research",
  "topics": "misinformation,healthcare,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-02T22:58:59.000Z",
  "fetched_at": "2026-07-14T16:30:05.528Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3184",
  "original_url": "https://arxiv.org/abs/2606.04274v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}