{
  "id": "2610.35101",
  "title": "Spherical Brownian Diffusion for Language Modeling",
  "authors": "Andrea Miele, Ilija Bogunovic",
  "first_public": "2026-10-26",
  "added_at": "2026-11-02",
  "venue": "arXiv",
  "arxiv": "2610.35101",
  "paper_url": "https://arxiv.org/abs/2610.35101",
  "html_url": "https://arxiv.org/html/2610.35101v1",
  "lens": [
    "beyond-sequential",
    "continuous",
    "analysis"
  ],
  "representation": [
    "continuous-state"
  ],
  "computation": [
    "diffusion",
    "parallel"
  ],
  "training": [
    "pretraining",
    "supervised"
  ],
  "questions": [
    "architecture",
    "efficiency",
    "evaluation",
    "theory"
  ],
  "evidence": [
    "empirical",
    "formal"
  ],
  "modality": [
    "language",
    "symbolic"
  ],
  "summary": "Corrupts token embeddings with Brownian motion on a sphere and trains a model to recover clean tokens. Controlled comparisons separate the effect of the corruption process from the sampling method on Sudoku, math problems and text generation.",
  "provenance": "Primary-source literature review, 2026-11-02",
  "author_names": [
    "Andrea Miele",
    "Ilija Bogunovic"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.35101/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-35101",
  "citation_date": "2026-10-26",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.35101/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.35101/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.35101/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.35101/citation.csl.json",
  "pdf_url": "https://arxiv.org/pdf/2610.35101"
}