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"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"
} |