{
  "id": 6702088,
  "title": "RetroThinker: Enabling Retrospective Thinking in Speech LLMs",
  "url": "https://urgent.news/2026/09/10/retrothinker-enabling-retrospective-thinking-in-speech-llms",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-10T17:41:53.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.11864v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Speech large language models (SpeechLLMs) offer reduced latency and retain paralinguistic nuances that are typically lost in cascaded automatic speech recognition (ASR) and text-based LM architectures. However, they continue to lag behind text-only LLMs on complex reasoning tasks, while real-time spoken interaction imposes strict latency constraints. Although prior works employ Chain-of-Thought…",
  "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."
}