{
  "id": 18790,
  "url": "https://arxiv.org/abs/2608.11741v1",
  "title": "JieZi: A Large-Scale Expert-Audited Dataset and Benchmark for Ancient Chinese Character Exegesis",
  "summary": "The scholarly exegesis of ancient Chinese characters demands integrating visual observation, linguistic analysis, and historical context. However, existing computational approaches focus narrowly on subtasks such as character recognition and retrieval, lacking the structured datasets and benchmarks required for comprehensive scholarly analysis. To address this limitation, we introduce Ancient Chinese Character Exegesis (ACCE), a vision-language question answering (VQA) task that models the schol",
  "authors": "Ran Li, Huiguo He, Jiahuan Cao, Junle Liu, Hiuyi Cheng, Lianwen Jin",
  "category": "research",
  "topics": "transparency",
  "orgs": null,
  "regions": "china",
  "published_at": "2026-08-12T07:30:00.000Z",
  "fetched_at": "2026-08-13T05:10:37.786Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/18790",
  "original_url": "https://arxiv.org/abs/2608.11741v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}