{
  "id": 11339935,
  "title": "ProtoFlow: Prototype-Guided Flow Matching for Multivariate Time Series Forecasting",
  "url": "https://urgent.news/2026/10/01/protoflow-prototype-guided-flow-matching-for-multivariate-time-series",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-01T08:48:18.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.01320v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Generative modeling has shown strong promise for multivariate time mseries (MTS) forecasting, especially scale to high-dimensional settings. Diffusion-based methods achieve competitive performance but typically require many sampling steps at inference. VAE-based non-iterative forecasting frameworks have therefore emerged as an efficient alternative. Within this line of work, vector quantization…",
  "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."
}