{
  "id": "2610.27559",
  "title": "Exploring Recurrent-Depth Language Models for Multitask Clinical Text Processing",
  "authors": "Xi Yang, Guodong Liu, Cheng Peng, Kaleb E. Smith, Yingying Zhang, Xing He, Yi Guo, Jiang Bian, Haoteng Tang, Yonghui Wu",
  "first_public": "2026-10-20",
  "added_at": "2026-10-22",
  "venue": "arXiv",
  "arxiv": "2610.27559",
  "paper_url": "https://arxiv.org/abs/2610.27559",
  "lens": [
    "recurrent",
    "analysis"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "recurrent",
    "hierarchical",
    "depth-wise"
  ],
  "training": [
    "supervised"
  ],
  "questions": [
    "evaluation",
    "generalization"
  ],
  "evidence": [
    "empirical"
  ],
  "modality": [
    "language"
  ],
  "summary": "Jointly fine-tunes looped and hierarchical recurrent language models on nine clinical text datasets and tests transfer to four more. Compares direct-answer performance with standard transformers while noting that the model families also differ in pretraining.",
  "provenance": "Primary-source literature review, 2026-10-22",
  "author_names": [
    "Xi Yang",
    "Guodong Liu",
    "Cheng Peng",
    "Kaleb E. Smith",
    "Yingying Zhang",
    "Xing He",
    "Yi Guo",
    "Jiang Bian",
    "Haoteng Tang",
    "Yonghui Wu"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.27559/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-27559",
  "citation_date": "2026-10-20",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.27559/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.27559/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.27559/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.27559/citation.csl.json",
  "pdf_url": "https://arxiv.org/pdf/2610.27559"
}