{
  "id": 13858731,
  "title": "ReplaySSM: Cache SSM Inputs, Not State",
  "url": "https://urgent.news/2026/10/09/replayssm-cache-ssm-inputs-not-state",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-09T15:59:40.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.13778v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "State-space models (SSMs) maintain a fixed-size recurrent state, but reading and writing it at every decoding step can bottleneck hybrid models. This eager state management causes large state I/O with low arithmetic intensity, leaves speculative decoding no cheap rollback, and feeds state quantization error into subsequent recurrent updates. We introduce ReplaySSM, which unrolls the recurrence to…",
  "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."
}