logbook.json

{
  "schema_version": 1,
  "title": "Repro - A Random Matrix Theory Perspective on the Consistency of Diffusion Models",
  "emoji": "🎯",
  "space_id": "ConductorAILabs/repro-rmt-diffusion-consistency",
  "paper": {
    "arxiv_id": "2602.02908"
  },
  "tags": [
    "icml2026-repro",
    "paper-iPjuUQbkfl"
  ],
  "updated_at": "2026-07-17T11:32:08+00:00",
  "root": {
    "slug": "index",
    "title": "Repro - A Random Matrix Theory Perspective on the Consistency of Diffusion Models",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "claim-1-rmt-framework-for-denoiser-mean-and-variance",
        "title": "Claim 1: RMT framework for denoiser mean and variance",
        "file": "pages/claim-1-rmt-framework-for-denoiser-mean-and-variance/page.md",
        "children": []
      },
      {
        "slug": "claim-2-noise-renormalization-via-self-consistent-kappa",
        "title": "Claim 2: Noise renormalization via self-consistent kappa",
        "file": "pages/claim-2-noise-renormalization-via-self-consistent-kappa/page.md",
        "children": []
      },
      {
        "slug": "claim-3-linear-theory-sharpness-and-unet-dit-validation",
        "title": "Claim 3: Linear theory sharpness and UNet/DiT validation",
        "file": "pages/claim-3-linear-theory-sharpness-and-unet-dit-validation/page.md",
        "children": []
      },
      {
        "slug": "methods-provenance-and-independence",
        "title": "Methods, provenance, and independence",
        "file": "pages/methods-provenance-and-independence/page.md",
        "children": []
      },
      {
        "slug": "failure-boundaries",
        "title": "Failure boundaries",
        "file": "pages/failure-boundaries/page.md",
        "children": []
      },
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      }
    ]
  },
  "agent_view_tokens": 9739,
  "revision": "1784287928621299000"
}