{
  "id": 18330,
  "url": "https://arxiv.org/abs/2608.08309v1",
  "title": "Three Necessary Principles for Self-Supervised Visual Representation Learning",
  "summary": "We argue that learning visual representations without labels requires a training signal jointly complete across three non-overlapping objectives: semantic invariance across augmented views, patch-level spatial prediction, and representational non-degeneracy. We formalize these as the observation, prediction, and regularization principles and prove (i) that combining observation and prediction without regularization admits the constant encoder as a global minimizer under negative-free alignment;",
  "authors": "Nikos Giakoumoglou, Paschalis Giakoumoglou, Tania Stathaki",
  "category": "research",
  "topics": "safety-alignment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-08T19:37:05.000Z",
  "fetched_at": "2026-08-11T05:10:37.351Z",
  "source_slug": "arxiv-cslg",
  "source_name": "arXiv cs.LG",
  "source_homepage": "https://arxiv.org/list/cs.LG/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/18330",
  "original_url": "https://arxiv.org/abs/2608.08309v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}