{
  "id": 15838739,
  "title": "Evolving Semantic Indexes for Generative Retrieval",
  "url": "https://urgent.news/2026/10/20/evolving-semantic-indexes-for-generative-retrieval",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-20T17:27:46.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.28568v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Generative retrieval (GR) casts search and recommendation as autoregressive generation of discrete semantic identifiers (SIDs). SID design largely determines GR quality, but its discrete, interdependent components (SID construction, collision handling, decoding, and training) cannot be optimized end-to-end with gradients and remain largely hand-designed. We introduce a framework that improves…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}