{
  "id": 6832,
  "url": "https://arxiv.org/abs/2603.22690v1",
  "title": "WiFi2Cap: Semantic Action Captioning from Wi-Fi CSI via Limb-Level Semantic Alignment",
  "summary": "Privacy-preserving semantic understanding of human activities is important for indoor sensing, yet existing Wi-Fi CSI-based systems mainly focus on pose estimation or predefined action classification rather than fine-grained language generation. Mapping CSI to natural-language descriptions remains challenging because of the semantic gap between wireless signals and language and direction-sensitive ambiguities such as left/right limb confusion. We propose WiFi2Cap, a three-stage framework for gen",
  "authors": "Tzu-Ti Wei, Chu-Yu Huang, Yu-Chee Tseng, Jen-Jee Chen",
  "category": "research",
  "topics": "safety-alignment,privacy-surveillance",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-24T01:30:46.000Z",
  "fetched_at": "2026-07-14T16:32:45.895Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6832",
  "original_url": "https://arxiv.org/abs/2603.22690v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}