{ "schema_version": 1, "title": "Repro: High-accuracy sampling for diffusion models and log-concave distributions", "emoji": "🎯", "space_id": "nkapila6/71132", "paper": null, "tags": [ "icml2026-repro", "paper-71132", "diffusion", "sampling", "theory" ], "updated_at": "2026-07-16T10:30:54+00:00", "root": { "slug": "index", "title": "Repro: High-accuracy sampling for diffusion models and log-concave distributions", "file": "pages/index.md", "children": [ { "slug": "00-scorecard", "title": "00 - Scorecard", "file": "pages/00-scorecard/page.md", "children": [] }, { "slug": "sources-protocol", "title": "Sources & Protocol", "file": "pages/sources-protocol/page.md", "children": [] }, { "slug": "c1-polylog-convergence-theorem-4-3", "title": "C1: Polylog convergence (Theorem 4.3)", "file": "pages/c1-polylog-convergence-theorem-4-3/page.md", "children": [] }, { "slug": "c2-minimal-data-complexity-o-d-polylog-1-delta", "title": "C2: Minimal data complexity O~(d polylog(1/delta))", "file": "pages/c2-minimal-data-complexity-o-d-polylog-1-delta/page.md", "children": [] }, { "slug": "c3-intrinsic-dimension-d-reduces-complexity", "title": "C3: Intrinsic dimension d* reduces complexity", "file": "pages/c3-intrinsic-dimension-d-reduces-complexity/page.md", "children": [] }, { "slug": "c4-non-uniform-lipschitz-complexity", "title": "C4: Non-uniform Lipschitz complexity", "file": "pages/c4-non-uniform-lipschitz-complexity/page.md", "children": [] }, { "slug": "c5-log-concave-sampling-with-polylog-accuracy", "title": "C5: Log-concave sampling with polylog accuracy", "file": "pages/c5-log-concave-sampling-with-polylog-accuracy/page.md", "children": [] }, { "slug": "conclusion", "title": "Conclusion", "file": "pages/conclusion/page.md", "children": [] } ] }, "agent_view_tokens": 1666, "revision": "1784197854429787000" }