{
  "id": 3634513,
  "title": "Unlocking Multimodal Protein Language Models at Inference Time",
  "url": "https://urgent.news/2026/08/26/unlocking-multimodal-protein-language-models-at-inference-time",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-26T14:29:06.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.25855v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Multimodal protein language models (pLMs) learn joint protein sequence-structure distributions, and their generation performance should also depend critically on inference-time sampling strategies. Yet prior work has focused more on model training than on how inference-time strategies behave. In this paper, we establish a three-stage investigation framework to empirically study the inference…",
  "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."
}