{
  "id": 6561,
  "url": "https://arxiv.org/abs/2603.29386v1",
  "title": "PromptForge-350k: A Large-Scale Dataset and Contrastive Framework for Prompt-Based AI Image Forgery Localization",
  "summary": "The rapid democratization of prompt-based AI image editing has recently exacerbated the risks associated with malicious content fabrication and misinformation. However, forgery localization methods targeting these emerging editing techniques remain significantly under-explored. To bridge this gap, we first introduce a fully automated mask annotating framework that leverages keypoint alignment and semantic space similarity to generate precise ground-truth masks for edited regions. Based on this f",
  "authors": "Jianpeng Wang, Haoyu Wang, Baoying Chen, Jishen Zeng, Yiming Qin, Yiqi Yang et al.",
  "category": "research",
  "topics": "safety-alignment,misinformation",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-31T07:54:58.000Z",
  "fetched_at": "2026-07-14T16:32:33.103Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6561",
  "original_url": "https://arxiv.org/abs/2603.29386v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}