{
  "id": 3263,
  "url": "https://arxiv.org/abs/2606.28343v1",
  "title": "The Crowded Embedding Space: A Mean-Field Mechanism for Emergent Marginalization in Retrieval-Augmented Agents",
  "summary": "Retrieval-augmented generative agents rely on retrieval for grounding, yet are typically evaluated on a query-by-query basis. This isolates interactions that are geometrically coupled in a shared embedding space. For example, we show that the high document density required to serve majority interests (e.g., generic \"Crime\" movies) can geometrically overcrowd the retrieval neighborhood of a semantically similar minority (e.g., \"Film Noir\"), effectively expelling minority content from top-$k$ resu",
  "authors": "Shwan Ashrafi, Dan Roth",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-01T20:40:30.000Z",
  "fetched_at": "2026-07-14T16:30:09.958Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3263",
  "original_url": "https://arxiv.org/abs/2606.28343v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}