{
  "id": 19474,
  "url": "https://arxiv.org/abs/2608.13190v1",
  "title": "ProME: Prototype-Margin Environments with Repair-Aware Selection for Group-Robust Learning",
  "summary": "Group-robust learning is crucial for maintaining accuracy on rare subpopulations when training-group labels are unavailable. However, existing methods often infer environments from a separate reference model and select representations before fitting the classifier used at deployment, leaving both decisions misaligned with the deployed predictor. In this work, we formulate group robustness without training-group labels as the endogenous environments with repair-aware selection (ERAS) problem, and",
  "authors": "Qianqian Wang, Yunshan Li, Dawei Huang, Wenwu Gong, Lili Yang",
  "category": "research",
  "topics": "safety-alignment,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-13T12:57:41.000Z",
  "fetched_at": "2026-08-14T05:10:49.168Z",
  "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/19474",
  "original_url": "https://arxiv.org/abs/2608.13190v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}