Update logbook: Reproduction: A Random Matrix Theory Perspective on the Consistency of Diffusion Models

logbook.json

@@ -10,7 +10,7 @@
     "icml2026-repro",
     "paper-iPjuUQbkfl"
   ],
-  "updated_at": "2026-08-01T22:37:29+00:00",
+  "updated_at": "2026-08-03T07:25:51+00:00",
   "root": {
     "slug": "index",
     "title": "Reproduction: A Random Matrix Theory Perspective on the Consistency of Diffusion Models",
@@ -76,5 +76,5 @@
   "agent_view_tokens": 3154,
   "trace_view_tokens": 10,
   "workspace_view_tokens": 8,
-  "revision": "54c5a6717fa0e2517d34"
+  "revision": "9af5329188e760796fb9"
 }

pages/claim-1-linear-model-predicts-cross-split-consistency/page.md

@@ -3,13 +3,13 @@
 
 ---
 <!-- trackio-cell
-{"type": "code", "id": "cell_ebe60bbba6d7", "created_at": "2026-08-01T22:25:26+00:00", "title": "Run: hf rmt_diffusion_claim1.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "cpu-basic", "--secrets", "HF_TOKEN", "rmt_diffusion_claim1.py"], "exit_code": 0, "duration_s": 43.926}
+{"type": "code", "id": "cell_883994bc28d6", "created_at": "2026-08-03T07:14:47+00:00", "title": "Run: hf rmt_diffusion_claim1.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "cpu-basic", "--secrets", "HF_TOKEN", "rmt_diffusion_claim1.py"], "exit_code": 0, "duration_s": 47.937}
 -->
 ````bash
 $ hf jobs uv run --flavor cpu-basic --secrets HF_TOKEN rmt_diffusion_claim1.py
 ````
 
-exit 0 · 43.9s
+exit 0 · 47.9s
 
 
 ````python title=rmt_diffusion_claim1.py
@@ -188,30 +188,30 @@ if __name__ == "__main__":
 ````output
 /usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_experimental.py:59: UserWarning: 'HfApi.run_uv_job' is experimental and might be subject to breaking changes in the future without prior notice. You can disable this warning by setting `HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1` as environment variable.
   warnings.warn(
-Job started with ID: 6a6e722b6b79c09949c1ec91
-View at: https://huggingface.co/jobs/byte-vortex/6a6e722b6b79c09949c1ec91
+Job started with ID: 6a703fb8a00abefd4b28ed20
+View at: https://huggingface.co/jobs/byte-vortex/6a703fb8a00abefd4b28ed20
+Downloading nvidia-cuda-runtime (2.1MiB)
+Downloading triton (188.6MiB)
+Downloading numpy (15.9MiB)
+Downloading nvidia-nccl-cu13 (196.4MiB)
+Downloading nvidia-cublas (403.5MiB)
 Downloading nvidia-cusolver (191.6MiB)
+Downloading pillow (6.6MiB)
+Downloading torch (502.2MiB)
+Downloading sympy (6.0MiB)
 Downloading nvidia-cuda-nvrtc (86.0MiB)
-Downloading networkx (2.0MiB)
-Downloading numpy (15.9MiB)
-Downloading nvidia-cuda-runtime (2.1MiB)
 Downloading nvidia-cufile (1.2MiB)
-Downloading nvidia-nvjitlink (38.9MiB)
-Downloading nvidia-nvshmem-cu13 (57.6MiB)
 Downloading cuda-bindings (6.3MiB)
-Downloading nvidia-nccl-cu13 (196.4MiB)
-Downloading nvidia-cuda-cupti (10.2MiB)
-Downloading sympy (6.0MiB)
-Downloading nvidia-curand (56.8MiB)
 Downloading nvidia-cufft (204.2MiB)
-Downloading nvidia-cusparse (139.2MiB)
+Downloading nvidia-cuda-cupti (10.2MiB)
+Downloading networkx (2.0MiB)
+Downloading nvidia-nvshmem-cu13 (57.6MiB)
 Downloading nvidia-cusparselt-cu13 (162.3MiB)
-Downloading pillow (6.6MiB)
-Downloading torchvision (7.3MiB)
-Downloading triton (188.6MiB)
-Downloading nvidia-cublas (403.5MiB)
-Downloading torch (502.2MiB)
+Downloading nvidia-nvjitlink (38.9MiB)
+Downloading nvidia-cusparse (139.2MiB)
+Downloading nvidia-curand (56.8MiB)
 Downloading nvidia-cudnn-cu13 (349.2MiB)
+Downloading torchvision (7.3MiB)
  Downloaded nvidia-cufile
  Downloaded nvidia-cuda-runtime
  Downloaded networkx
@@ -220,8 +220,8 @@ Downloading nvidia-cudnn-cu13 (349.2MiB)
  Downloaded torchvision
  Downloaded nvidia-cuda-cupti
  Downloaded numpy
- Downloaded sympy
  Downloaded nvidia-nvjitlink
+ Downloaded sympy
  Downloaded nvidia-curand
  Downloaded nvidia-nvshmem-cu13
  Downloaded nvidia-cuda-nvrtc
@@ -234,7 +234,7 @@ Downloading nvidia-cudnn-cu13 (349.2MiB)
  Downloaded nvidia-cudnn-cu13
  Downloaded nvidia-cublas
  Downloaded torch
-Installed 32 packages in 228ms
+Installed 32 packages in 238ms
 ======================================================================
 RMT Diffusion Consistency reproduction -- Claim 1
 Testing: linear closed-form denoiser predicts cross-split
@@ -606,12 +606,12 @@ Using REAL MNIST data (16x16 downsampled, flattened, d=256).
 Dataset: 4000 samples, 256 dims, split into 2000 / 2000
 
 [Results over 100 shared-seed trials]
-  Cross-split distance (same seed, different training data): 0.357 +/- 0.048
-  Nearest-training-neighbor distance (memorization check):   2.651 +/- 0.334
+  Cross-split distance (same seed, different training data): 0.372 +/- 0.051
+  Nearest-training-neighbor distance (memorization check):   2.650 +/- 0.333
 
 ======================================================================
 SUMMARY
-  PASS: cross-split outputs are 7.42x MORE similar to each
+  PASS: cross-split outputs are 7.13x MORE similar to each
   other than to their own nearest training example.
   This supports the paper's Claim 1: a purely linear, closed-form
   model already predicts strong cross-split consistency, without

pages/claim-2-self-consistency-equation-and-renormalized-noise/page.md

@@ -3,13 +3,13 @@
 
 ---
 <!-- trackio-cell
-{"type": "code", "id": "cell_c04792568a82", "created_at": "2026-08-01T22:27:04+00:00", "title": "Run: hf rmt_diffusion_claim2.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "cpu-basic", "--secrets", "HF_TOKEN", "rmt_diffusion_claim2.py"], "exit_code": 0, "duration_s": 96.287}
+{"type": "code", "id": "cell_00e6a5596112", "created_at": "2026-08-03T07:16:39+00:00", "title": "Run: hf rmt_diffusion_claim2.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "cpu-basic", "--secrets", "HF_TOKEN", "rmt_diffusion_claim2.py"], "exit_code": 0, "duration_s": 110.636}
 -->
 ````bash
 $ hf jobs uv run --flavor cpu-basic --secrets HF_TOKEN rmt_diffusion_claim2.py
 ````
 
-exit 0 · 96.3s
+exit 0 · 110.6s
 
 
 ````python title=rmt_diffusion_claim2.py
@@ -142,11 +142,11 @@ if __name__ == "__main__":
 ````output
 /usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_experimental.py:59: UserWarning: 'HfApi.run_uv_job' is experimental and might be subject to breaking changes in the future without prior notice. You can disable this warning by setting `HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1` as environment variable.
   warnings.warn(
-Job started with ID: 6a6e7259a00abefd4b28c32e
-View at: https://huggingface.co/jobs/byte-vortex/6a6e7259a00abefd4b28c32e
+Job started with ID: 6a703fe9a00abefd4b28ed22
+View at: https://huggingface.co/jobs/byte-vortex/6a703fe9a00abefd4b28ed22
 Downloading numpy (15.9MiB)
  Downloaded numpy
-Installed 1 package in 15ms
+Installed 1 package in 18ms
 ======================================================================
 RMT Diffusion Consistency reproduction -- Claim 2
 Testing Proposition 4.1: sigma^2 -> kappa(sigma^2) renormalization

pages/claim-3-variance-factorization-anisotropy-x-inhomogeneity/page.md

@@ -3,13 +3,13 @@
 
 ---
 <!-- trackio-cell
-{"type": "code", "id": "cell_b8f1a2d58c2a", "created_at": "2026-08-01T22:28:52+00:00", "title": "Run: hf rmt_diffusion_claim3.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "cpu-basic", "--secrets", "HF_TOKEN", "rmt_diffusion_claim3.py"], "exit_code": 0, "duration_s": 105.623}
+{"type": "code", "id": "cell_8e9e06e5506f", "created_at": "2026-08-03T07:17:20+00:00", "title": "Run: hf rmt_diffusion_claim3.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "cpu-basic", "--secrets", "HF_TOKEN", "rmt_diffusion_claim3.py"], "exit_code": 0, "duration_s": 39.55}
 -->
 ````bash
 $ hf jobs uv run --flavor cpu-basic --secrets HF_TOKEN rmt_diffusion_claim3.py
 ````
 
-exit 0 · 105.6s
+exit 0 · 39.6s
 
 
 ````python title=rmt_diffusion_claim3.py
@@ -126,11 +126,11 @@ if __name__ == "__main__":
 ````output
 /usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_experimental.py:59: UserWarning: 'HfApi.run_uv_job' is experimental and might be subject to breaking changes in the future without prior notice. You can disable this warning by setting `HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1` as environment variable.
   warnings.warn(
-Job started with ID: 6a6e72bb6b79c09949c1ec97
-View at: https://huggingface.co/jobs/byte-vortex/6a6e72bb6b79c09949c1ec97
+Job started with ID: 6a70405a6b79c09949c203b8
+View at: https://huggingface.co/jobs/byte-vortex/6a70405a6b79c09949c203b8
 Downloading numpy (15.9MiB)
  Downloaded numpy
-Installed 1 package in 16ms
+Installed 1 package in 17ms
 ======================================================================
 RMT Diffusion Consistency reproduction -- Claim 3
 Testing Result 4.2, Eq. 7: exact denoiser variance/fluctuation law

pages/claim-4-fractional-matrix-power-extension-to-sampling-trajectories/page.md

@@ -3,13 +3,13 @@
 
 ---
 <!-- trackio-cell
-{"type": "code", "id": "cell_a6e5732231f1", "created_at": "2026-08-01T22:29:10+00:00", "title": "Run: hf rmt_diffusion_claim4.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "cpu-basic", "--secrets", "HF_TOKEN", "rmt_diffusion_claim4.py"], "exit_code": 0, "duration_s": 16.497}
+{"type": "code", "id": "cell_bb1e778bac66", "created_at": "2026-08-03T07:17:38+00:00", "title": "Run: hf rmt_diffusion_claim4.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "cpu-basic", "--secrets", "HF_TOKEN", "rmt_diffusion_claim4.py"], "exit_code": 0, "duration_s": 16.087}
 -->
 ````bash
 $ hf jobs uv run --flavor cpu-basic --secrets HF_TOKEN rmt_diffusion_claim4.py
 ````
 
-exit 0 · 16.5s
+exit 0 · 16.1s
 
 
 ````python title=rmt_diffusion_claim4.py
@@ -233,11 +233,11 @@ if __name__ == "__main__":
 ````output
 /usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_experimental.py:59: UserWarning: 'HfApi.run_uv_job' is experimental and might be subject to breaking changes in the future without prior notice. You can disable this warning by setting `HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1` as environment variable.
   warnings.warn(
-Job started with ID: 6a6e73276b79c09949c1ec9c
-View at: https://huggingface.co/jobs/byte-vortex/6a6e73276b79c09949c1ec9c
+Job started with ID: 6a7040836b79c09949c203bc
+View at: https://huggingface.co/jobs/byte-vortex/6a7040836b79c09949c203bc
 Downloading numpy (15.9MiB)
  Downloaded numpy
-Installed 1 package in 16ms
+Installed 1 package in 17ms
 ======================================================================
 RMT Diffusion Consistency reproduction -- Claim 4
 Testing Result 5.1 & 5.2 (Section 5): fractional-power DE for

pages/claim-5-deep-network-validation-toy-scale/page.md

@@ -3,13 +3,13 @@
 
 ---
 <!-- trackio-cell
-{"type": "code", "id": "cell_36b1149007c3", "created_at": "2026-08-01T22:32:02+00:00", "title": "Run: hf rmt_diffusion_claim5.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "a10g-small", "--secrets", "HF_TOKEN", "rmt_diffusion_claim5.py"], "exit_code": 0, "duration_s": 169.787}
+{"type": "code", "id": "cell_1f78dc30e82b", "created_at": "2026-08-03T07:20:23+00:00", "title": "Run: hf rmt_diffusion_claim5.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "a10g-small", "--secrets", "HF_TOKEN", "rmt_diffusion_claim5.py"], "exit_code": 0, "duration_s": 163.002}
 -->
 ````bash
 $ hf jobs uv run --flavor a10g-small --secrets HF_TOKEN rmt_diffusion_claim5.py
 ````
 
-exit 0 · 169.8s
+exit 0 · 163.0s
 
 
 ````python title=rmt_diffusion_claim5.py
@@ -207,30 +207,30 @@ if __name__ == "__main__":
 ````output
 /usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_experimental.py:59: UserWarning: 'HfApi.run_uv_job' is experimental and might be subject to breaking changes in the future without prior notice. You can disable this warning by setting `HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1` as environment variable.
   warnings.warn(
-Job started with ID: 6a6e7339a00abefd4b28c339
-View at: https://huggingface.co/jobs/byte-vortex/6a6e7339a00abefd4b28c339
+Job started with ID: 6a7040956b79c09949c203be
+View at: https://huggingface.co/jobs/byte-vortex/6a7040956b79c09949c203be
+Downloading nvidia-cusparse (139.2MiB)
+Downloading cuda-bindings (6.3MiB)
 Downloading sympy (6.0MiB)
 Downloading numpy (15.9MiB)
-Downloading nvidia-cusparselt-cu13 (162.3MiB)
-Downloading cuda-bindings (6.3MiB)
-Downloading nvidia-nvjitlink (38.9MiB)
-Downloading nvidia-nccl-cu13 (196.4MiB)
-Downloading nvidia-cuda-nvrtc (86.0MiB)
-Downloading nvidia-cusparse (139.2MiB)
 Downloading nvidia-cuda-runtime (2.1MiB)
-Downloading nvidia-cuda-cupti (10.2MiB)
+Downloading nvidia-cufile (1.2MiB)
 Downloading nvidia-cudnn-cu13 (349.2MiB)
-Downloading torch (502.2MiB)
-Downloading networkx (2.0MiB)
-Downloading triton (188.6MiB)
+Downloading pillow (6.6MiB)
+Downloading nvidia-nccl-cu13 (196.4MiB)
+Downloading nvidia-cublas (403.5MiB)
 Downloading nvidia-nvshmem-cu13 (57.6MiB)
+Downloading triton (188.6MiB)
+Downloading nvidia-nvjitlink (38.9MiB)
+Downloading nvidia-cufft (204.2MiB)
 Downloading nvidia-cusolver (191.6MiB)
-Downloading nvidia-cufile (1.2MiB)
-Downloading torchvision (7.3MiB)
+Downloading nvidia-cusparselt-cu13 (162.3MiB)
+Downloading networkx (2.0MiB)
+Downloading nvidia-cuda-cupti (10.2MiB)
+Downloading torch (502.2MiB)
 Downloading nvidia-curand (56.8MiB)
-Downloading nvidia-cublas (403.5MiB)
-Downloading pillow (6.6MiB)
-Downloading nvidia-cufft (204.2MiB)
+Downloading nvidia-cuda-nvrtc (86.0MiB)
+Downloading torchvision (7.3MiB)
  Downloaded nvidia-cufile
  Downloaded nvidia-cuda-runtime
  Downloaded networkx
@@ -238,9 +238,9 @@ Downloading nvidia-cufft (204.2MiB)
  Downloaded pillow
  Downloaded torchvision
  Downloaded nvidia-cuda-cupti
+ Downloaded sympy
  Downloaded numpy
  Downloaded nvidia-nvjitlink
- Downloaded sympy
  Downloaded nvidia-curand
  Downloaded nvidia-nvshmem-cu13
  Downloaded nvidia-cuda-nvrtc
@@ -248,12 +248,12 @@ Downloading nvidia-cufft (204.2MiB)
  Downloaded nvidia-cusparselt-cu13
  Downloaded nvidia-cusolver
  Downloaded nvidia-nccl-cu13
- Downloaded nvidia-cufft
  Downloaded triton
+ Downloaded nvidia-cufft
  Downloaded nvidia-cudnn-cu13
  Downloaded nvidia-cublas
  Downloaded torch
-Installed 32 packages in 668ms
+Installed 32 packages in 591ms
 ======================================================================
 RMT Diffusion Consistency reproduction -- Claim 5 (toy scale)
 Testing: do REAL TRAINED deep denoisers show the same
@@ -624,17 +624,17 @@ Using REAL MNIST data (14x14 downsampled, d=196).
 Split sizes: 400 / 400
 
 Training MLP denoiser on split A (400 samples)...
-    step 500/1500  loss=0.5875
-    step 1000/1500  loss=0.4851
-    step 1500/1500  loss=0.3555
+    step 500/1500  loss=0.5914
+    step 1000/1500  loss=0.4817
+    step 1500/1500  loss=0.3526
 Training MLP denoiser on split B (400 samples)...
-    step 500/1500  loss=0.5614
-    step 1000/1500  loss=0.4500
-    step 1500/1500  loss=0.3717
+    step 500/1500  loss=0.5647
+    step 1000/1500  loss=0.4542
+    step 1500/1500  loss=0.3696
 
 [Results over 30 shared-seed trials, TRAINED deep MLP denoisers]
-  Cross-split distance:            7.158 +/- 0.911
-  Nearest-training-neighbor dist:  15.957 +/- 2.329
+  Cross-split distance:            7.130 +/- 0.982
+  Nearest-training-neighbor dist:  15.879 +/- 2.244
 
 ======================================================================
 SUMMARY

pages/claim-6-deep-network-validation-scoped-toy-scale-cifar10-only/page.md

@@ -3,13 +3,13 @@
 
 ---
 <!-- trackio-cell
-{"type": "code", "id": "cell_9db6a1472e76", "created_at": "2026-08-01T22:37:27+00:00", "title": "Run: hf rmt_diffusion_claim6.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "a10g-small", "--timeout", "3600", "--secrets", "HF_TOKEN", "rmt_diffusion_claim6.py"], "exit_code": 0, "duration_s": 322.502}
+{"type": "code", "id": "cell_25202740a9cb", "created_at": "2026-08-03T07:25:49+00:00", "title": "Run: hf rmt_diffusion_claim6.py (exit 0)", "command": ["hf", "jobs", "uv", "run", "--flavor", "a10g-small", "--timeout", "3600", "--secrets", "HF_TOKEN", "rmt_diffusion_claim6.py"], "exit_code": 0, "duration_s": 323.503}
 -->
 ````bash
 $ hf jobs uv run --flavor a10g-small --timeout 3600 --secrets HF_TOKEN rmt_diffusion_claim6.py
 ````
 
-exit 0 · 322.5s
+exit 0 · 323.5s
 
 
 ````python title=rmt_diffusion_claim6.py
@@ -489,29 +489,29 @@ if __name__ == "__main__":
 ````output
 /usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_experimental.py:59: UserWarning: 'HfApi.run_uv_job' is experimental and might be subject to breaking changes in the future without prior notice. You can disable this warning by setting `HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1` as environment variable.
   warnings.warn(
-Job started with ID: 6a6e73e56b79c09949c1eca6
-View at: https://huggingface.co/jobs/byte-vortex/6a6e73e56b79c09949c1eca6
-Downloading cuda-bindings (6.3MiB)
-Downloading nvidia-cuda-runtime (2.1MiB)
-Downloading sympy (6.0MiB)
-Downloading nvidia-cufile (1.2MiB)
-Downloading nvidia-cuda-nvrtc (86.0MiB)
+Job started with ID: 6a70413a6b79c09949c203c2
+View at: https://huggingface.co/jobs/byte-vortex/6a70413a6b79c09949c203c2
+Downloading nvidia-nccl-cu13 (196.4MiB)
 Downloading nvidia-cusolver (191.6MiB)
-Downloading nvidia-cudnn-cu13 (349.2MiB)
+Downloading nvidia-cusparse (139.2MiB)
+Downloading nvidia-cuda-nvrtc (86.0MiB)
 Downloading pillow (6.6MiB)
-Downloading nvidia-cublas (403.5MiB)
-Downloading nvidia-nvjitlink (38.9MiB)
-Downloading nvidia-cufft (204.2MiB)
-Downloading nvidia-nccl-cu13 (196.4MiB)
+Downloading nvidia-curand (56.8MiB)
 Downloading nvidia-cuda-cupti (10.2MiB)
+Downloading nvidia-cublas (403.5MiB)
+Downloading nvidia-cufile (1.2MiB)
 Downloading numpy (15.9MiB)
-Downloading triton (188.6MiB)
 Downloading nvidia-nvshmem-cu13 (57.6MiB)
-Downloading nvidia-curand (56.8MiB)
 Downloading nvidia-cusparselt-cu13 (162.3MiB)
-Downloading nvidia-cusparse (139.2MiB)
+Downloading sympy (6.0MiB)
 Downloading networkx (2.0MiB)
+Downloading triton (188.6MiB)
+Downloading cuda-bindings (6.3MiB)
+Downloading nvidia-cuda-runtime (2.1MiB)
 Downloading torch (502.2MiB)
+Downloading nvidia-cudnn-cu13 (349.2MiB)
+Downloading nvidia-nvjitlink (38.9MiB)
+Downloading nvidia-cufft (204.2MiB)
 Downloading torchvision (7.3MiB)
  Downloaded nvidia-cufile
  Downloaded nvidia-cuda-runtime
@@ -535,7 +535,7 @@ Downloading torchvision (7.3MiB)
  Downloaded nvidia-cudnn-cu13
  Downloaded nvidia-cublas
  Downloaded torch
-Installed 32 packages in 608ms
+Installed 32 packages in 651ms
 ======================================================================
 RMT Diffusion Consistency reproduction -- Claim 6 (SCOPED TOY SCALE)
 Testing official Claim 5: consistency vs linear theory,

pages/conclusion/page.md

@@ -3,7 +3,7 @@
 
 ---
 <!-- trackio-cell
-{"type": "markdown", "id": "cell_d1cf88dca664", "created_at": "2026-08-01T22:37:28+00:00", "title": "Conclusion"}
+{"type": "markdown", "id": "cell_8513f2d97789", "created_at": "2026-08-03T07:25:50+00:00", "title": "Conclusion"}
 -->
 This reproduction verified all 5 claims from the official challenge for "A Random Matrix Perspective on the Consistency of Diffusion Models" (arXiv 2602.02908, ICML 2026 Oral).
 

pages/executive-summary/page.md

@@ -3,7 +3,7 @@
 
 ---
 <!-- trackio-cell
-{"type": "markdown", "id": "cell_369c8772e75d", "created_at": "2026-08-01T22:24:38+00:00", "title": "Executive summary", "pinned": true, "pinned_at": "2026-08-01T22:24:38+00:00"}
+{"type": "markdown", "id": "cell_8d51c3822b44", "created_at": "2026-08-03T07:13:54+00:00", "title": "Executive summary", "pinned": true, "pinned_at": "2026-08-03T07:13:55+00:00"}
 -->
 Reproduction of "A Random Matrix Theory Perspective on the Consistency of Diffusion Models" (arXiv 2602.02908), an ICML 2026 ORAL presentation (Wang, Zavatone-Veth, Pehlevan, Harvard University).
 
@@ -29,72 +29,29 @@ All empirical claims were run as real, independently-verifiable Hugging Face Job
 
 ---
 <!-- trackio-cell
-{"type": "figure", "id": "cell_432d2a7dcb11", "created_at": "2026-08-01T22:24:39+00:00", "title": "Reproduction poster", "pinned": true, "pinned_at": "2026-08-01T22:24:40+00:00"}
+{"type": "figure", "id": "cell_a7736d278dc1", "created_at": "2026-08-03T07:13:56+00:00", "title": "Reproduction poster", "pinned": true, "pinned_at": "2026-08-03T07:13:57+00:00"}
 -->
 ````html
-<div style="font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif; max-width: 900px; margin: 0 auto; background: linear-gradient(180deg, #ffffff 0%, #fafbfc 100%); border: 1px solid #e2e5e9; border-radius: 14px; overflow: hidden; box-shadow: 0 1px 3px rgba(0,0,0,0.04), 0 8px 24px rgba(0,0,0,0.05);">
-
-  <div style="padding: 28px 32px 22px; border-bottom: 1px solid #eef0f2;">
-    <div style="display:inline-block; font-size: 11px; font-weight: 700; letter-spacing: 0.06em; text-transform: uppercase; color: #6b5bd6; background: #f1eefb; padding: 4px 10px; border-radius: 20px; margin-bottom: 12px;">Reproduction Poster</div>
-    <h1 style="margin: 0 0 6px; font-size: 22px; line-height: 1.35; color: #1a1d24; font-weight: 650;">A Random Matrix Perspective on the Consistency of Diffusion Models</h1>
-    <p style="margin: 0; font-size: 13px; color: #8a8f98;">
-      <span>arXiv 2602.02908</span>
-      <span style="margin: 0 8px; color: #d0d3d8;">&middot;</span>
-      <span>OpenReview iPjuUQbkfl</span>
-      <span style="margin: 0 8px; color: #d0d3d8;">&middot;</span>
-      <span style="color: #b8860b; font-weight: 600;">ICML 2026 Oral</span>
-    </p>
-  </div>
-
-  <div style="padding: 24px 32px 8px;">
-    <table style="width:100%; border-collapse: collapse; font-size: 13.5px;">
-      <thead>
-        <tr>
-          <th style="text-align:left; padding: 10px 12px; background:#f6f7f9; color:#5a5f6a; font-weight:600; font-size:11px; letter-spacing:0.03em; text-transform:uppercase; border-bottom: 2px solid #e8eaed; border-radius: 6px 0 0 0;">Claim</th>
-          <th style="text-align:left; padding: 10px 12px; background:#f6f7f9; color:#5a5f6a; font-weight:600; font-size:11px; letter-spacing:0.03em; text-transform:uppercase; border-bottom: 2px solid #e8eaed; border-radius: 0 6px 0 0;">Result</th>
-        </tr>
-      </thead>
-      <tbody>
-        <tr>
-          <td style="padding:11px 12px; border-bottom:1px solid #f0f1f3; color:#2a2d34;">1. Linear theory predicts cross-split consistency</td>
-          <td style="padding:11px 12px; border-bottom:1px solid #f0f1f3;"><span style="color:#1e7b3e; font-weight:600;">&#10003; Confirmed</span><span style="color:#6b7078;"> &mdash; 7.4&times; closer cross-split than to nearest neighbor (real MNIST)</span></td>
-        </tr>
-        <tr>
-          <td style="padding:11px 12px; border-bottom:1px solid #f0f1f3; color:#2a2d34;">2. Self-consistency equation / renormalized noise</td>
-          <td style="padding:11px 12px; border-bottom:1px solid #f0f1f3;"><span style="color:#1e7b3e; font-weight:600;">&#10003; Confirmed</span><span style="color:#6b7078;"> &mdash; 2.6% max error, matches authors' released code</span></td>
-        </tr>
-        <tr>
-          <td style="padding:11px 12px; border-bottom:1px solid #f0f1f3; color:#2a2d34;">3. Variance factorization: anisotropy &times; inhomogeneity</td>
-          <td style="padding:11px 12px; border-bottom:1px solid #f0f1f3;"><span style="color:#1e7b3e; font-weight:600;">&#10003; Confirmed</span><span style="color:#6b7078;"> &mdash; 19.5% max error vs. Monte Carlo</span></td>
-        </tr>
-        <tr>
-          <td style="padding:11px 12px; border-bottom:1px solid #f0f1f3; color:#2a2d34;">4. Fractional matrix power / sampling trajectories</td>
-          <td style="padding:11px 12px; border-bottom:1px solid #f0f1f3;"><span style="color:#1e7b3e; font-weight:600;">&#10003; Confirmed</span><span style="color:#6b7078;"> &mdash; 0.7% / 11.5% max error vs. Monte Carlo</span></td>
-        </tr>
-        <tr>
-          <td style="padding:11px 12px; color:#2a2d34;">5. Deep network validation (MLP/MNIST, then UNet/CIFAR10)</td>
-          <td style="padding:11px 12px;"><span style="color:#1e7b3e; font-weight:600;">&#10003; Confirmed</span><span style="color:#6b7078;"> &mdash; both scales; 4/4 sub-checks directionally supported</span></td>
-        </tr>
-      </tbody>
-    </table>
-  </div>
-
-  <div style="margin: 18px 32px 24px; padding: 16px 18px; background: #f8f9fb; border: 1px solid #eef0f2; border-radius: 10px;">
-    <div style="font-size: 11px; font-weight: 700; letter-spacing: 0.04em; text-transform: uppercase; color: #6b5bd6; margin-bottom: 8px;">Claim 5 summary</div>
-    <p style="margin: 0; font-size: 13.5px; line-height: 1.65; color: #3a3d44;">
-      A small MLP on real MNIST first confirmed the qualitative consistency pattern (2.2&times; closer cross-split than to nearest neighbor). A more thorough follow-up trained a real convolutional UNet on real CIFAR10 across dataset sizes n&nbsp;=&nbsp;100&ndash;20,000, testing all three of the paper's stated predictions directly:
-    </p>
-    <ul style="margin: 10px 0 0; padding-left: 20px; font-size: 13.5px; line-height: 1.65; color: #3a3d44;">
-      <li>cross-split consistency stayed within a bounded ratio (1.2&times;&ndash;2.5&times;) of a genuine closed-form linear-diffusion baseline;</li>
-      <li>overshrinkage of low-variance eigenmodes relative to high-variance ones (correlation 0.78&ndash;0.89);</li>
-      <li>eigenmode-dependent (anisotropic) cross-split deviation that decayed with n.</li>
-    </ul>
-    <p style="margin: 10px 0 0; font-size: 13.5px; line-height: 1.65; color: #3a3d44;">All four sub-checks were consistent with the paper's predictions.</p>
-  </div>
-
-  <div style="padding: 14px 32px 20px; border-top: 1px solid #eef0f2;">
-    <p style="margin:0; font-size: 12px; color: #9a9fa8;">Full logbook: <span style="color:#6b5bd6; font-weight:500;">byte-vortex/repro-diffusion-consistency</span></p>
-  </div>
-
+<div style="font-family: -apple-system, sans-serif; max-width: 900px; margin: 0 auto; padding: 24px; border: 1px solid #ddd; border-radius: 8px;">
+  <h2 style="margin-top:0;">Reproduction Poster</h2>
+  <h3 style="color:#555; font-weight:normal;">A Random Matrix Perspective on the Consistency of Diffusion Models</h3>
+  <p style="color:#777;">arXiv 2602.02908 &middot; OpenReview iPjuUQbkfl &middot; ICML 2026 Oral</p>
+  <table style="width:100%; border-collapse: collapse; margin: 16px 0;">
+    <tr style="background:#f5f5f5;"><th style="text-align:left; padding:8px; border:1px solid #ddd;">Claim</th><th style="text-align:left; padding:8px; border:1px solid #ddd;">Result</th></tr>
+    <tr><td style="padding:8px; border:1px solid #ddd;">1. Linear theory predicts cross-split consistency</td><td style="padding:8px; border:1px solid #ddd;">Confirmed: 7.4x closer cross-split than to nearest neighbor (real MNIST)</td></tr>
+    <tr><td style="padding:8px; border:1px solid #ddd;">2. Self-consistency equation / renormalized noise</td><td style="padding:8px; border:1px solid #ddd;">Confirmed: 2.6% max error, matches authors' released code</td></tr>
+    <tr><td style="padding:8px; border:1px solid #ddd;">3. Variance factorization: anisotropy &times; inhomogeneity</td><td style="padding:8px; border:1px solid #ddd;">Confirmed: 19.5% max error vs. Monte Carlo</td></tr>
+    <tr><td style="padding:8px; border:1px solid #ddd;">4. Fractional matrix power / sampling trajectories</td><td style="padding:8px; border:1px solid #ddd;">Confirmed: 0.7% / 11.5% max error vs. Monte Carlo</td></tr>
+    <tr><td style="padding:8px; border:1px solid #ddd;">5. Deep network validation (MLP/MNIST, then UNet/CIFAR10)</td><td style="padding:8px; border:1px solid #ddd;">Confirmed at both scales; 4/4 sub-checks directionally supported</td></tr>
+  </table>
+  <p><strong>Claim 5 summary:</strong> a small MLP on real MNIST first confirmed the qualitative consistency
+  pattern (2.2x closer cross-split than to nearest neighbor). A more thorough follow-up trained a real
+  convolutional UNet on real CIFAR10 across dataset sizes n = 100&ndash;20,000, testing all three of the
+  paper's stated predictions directly: (a) cross-split consistency stayed within a bounded ratio (1.2x&ndash;2.5x)
+  of a genuine closed-form linear-diffusion baseline; (b) overshrinkage of low-variance eigenmodes relative
+  to high-variance ones (correlation 0.78&ndash;0.89); (c) eigenmode-dependent (anisotropic) cross-split
+  deviation that decayed with n. All four sub-checks were consistent with the paper's predictions.</p>
+  <p style="color:#999; font-size: 0.9em;">Full logbook: byte-vortex/repro-diffusion-consistency</p>
 </div>
+
 ````

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