{
  "id": "2611.07226",
  "title": "Loopback Transformer: Towards a Unified View of Residual Looped Transformers",
  "authors": "Xuan Ouyang, Zefan Cai, Chenlong Zhang, Cheng Luo, Ke Wan, Junjie Hu",
  "first_public": "2026-11-04",
  "added_at": "2026-11-09",
  "venue": "arXiv",
  "arxiv": "2611.07226",
  "paper_url": "https://arxiv.org/abs/2611.07226",
  "html_url": "https://arxiv.org/html/2611.07226v1",
  "lens": [
    "recurrent",
    "analysis"
  ],
  "representation": [
    "hidden-state",
    "cache-memory"
  ],
  "computation": [
    "recurrent",
    "depth-wise"
  ],
  "training": [
    "pretraining"
  ],
  "questions": [
    "architecture",
    "theory",
    "scaling"
  ],
  "evidence": [
    "empirical",
    "formal"
  ],
  "modality": [
    "language"
  ],
  "summary": "Treats residual connections as memory across depth. Loopback keeps the original input separate, decays earlier block updates, and learns attention weights over those updates to control their contribution during repeated transformer passes.",
  "provenance": "Primary-source literature review, 2026-11-09",
  "author_names": [
    "Xuan Ouyang",
    "Zefan Cai",
    "Chenlong Zhang",
    "Cheng Luo",
    "Ke Wan",
    "Junjie Hu"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2611.07226/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2611-07226",
  "citation_date": "2026-11-04",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2611.07226/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2611.07226/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2611.07226/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2611.07226/citation.csl.json",
  "pdf_url": "https://arxiv.org/pdf/2611.07226"
}