{
  "id": 5970,
  "url": "https://arxiv.org/abs/2604.10960v2",
  "title": "RAG-KT: Cross-platform Explainable Knowledge Tracing with Multi-view Fusion Retrieval Generation",
  "summary": "Knowledge Tracing (KT) infers a student's knowledge state from past interactions to predict future performance. Conventional Deep Learning (DL)-based KT models are typically tied to platform-specific identifiers and latent representations, making them hard to transfer and interpret. Large Language Model (LLM)-based methods can be either ungrounded under prompting or overly domain-dependent under fine-tuning. In addition, most existing KT methods are developed and evaluated under a same-distribut",
  "authors": "Zhiyi Duan, Hongyu Yuan, Rui Liu",
  "category": "research",
  "topics": "children-education,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-13T03:56:17.000Z",
  "fetched_at": "2026-07-14T16:32:11.180Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5970",
  "original_url": "https://arxiv.org/abs/2604.10960v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}