Paper Citation Record · LEDGER

A Random Matrix Theory Perspective on the Consistency of Diffusion Models

As of 15 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 3 inbound Pith citation observations for arXiv:2602.02908.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2602.02908 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:17:24.237129Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-10T01:25:16.156790Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-10T01:26:43.158067Z

Reference resolution

23 of 23 outbound references displayed

verified exact0
verified fuzzy0
unresolved22
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ad5ab80c-a222-4c12-831d-8efc96d7159a · outbound

This paper cites In search of dispersed memories: Generative diffusion models are associative memory networks.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models In search of dispersed memories: Generative diffusion models are associative memory networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:22.426123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37dbc0fb-f760-4a1e-b5b8-c4075851a3cd · outbound

This paper cites An analytic theory of creativity in convolutional diffusion models.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models An analytic theory of creativity in convolutional diffusion models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:22.790370Z

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Observation b824a08f-4463-4672-90d0-7a6c26e472bd · outbound

This paper cites URL https://doi.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models URL https://doi

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:22.870373Z

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Observation 6551ac56-66d7-4caa-8de8-03ead16d7f8c · outbound

This paper cites Towards a Mechanistic Explanation of Diffusion Model Generalization.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models Towards a Mechanistic Explanation of Diffusion Model Generalization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.141789Z

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Observation 47e187b8-071c-4b04-839f-041527e17e9a · outbound

This paper cites Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.225861Z

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Observation cdc0b931-84fe-4c74-a70b-0334ed1c525a · outbound

This paper cites An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.429089Z

Source-reported events for the cited work

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Observation 5c50f859-510f-425a-8a56-2ada985744e8 · outbound

This paper cites The Hidden Linear Structure in Score-Based Models and its Application.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models The Hidden Linear Structure in Score-Based Models and its Application

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.595771Z

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Observation 9b4083ad-3ab8-4727-bf33-2c2b83c887cd · outbound

This paper cites LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.699429Z

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Observation b226f697-cf8c-41af-b148-deeaa8020b68 · outbound

This paper cites mosaics.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models mosaics

Reference 19

Resolution: malformed identifier; no resolver link, observed 2026-08-03T05:17:23.814244Z

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Observation a9d77ea9-b925-4c9b-b813-adfb825936c6 · outbound

This paper cites df 1(λ) := Tr[Σ(Σ+λI) −1](11) df 2(λ) := Tr[Σ2(Σ+λI) −2].(12) Note that df 2(κ)−df 1(κ) = Tr[Σ2(Σ+κI) −2]−Tr[Σ(Σ+κI) −1] = Tr[ Σ(Σ+κI) −1 −I Σ(Σ+κI) −1] =κTr[Σ(Σ+κI) −2] >0.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models df 1(λ) := Tr[Σ(Σ+λI) −1](11) df 2(λ) := Tr[Σ2(Σ+λI) −2].(12) Note that df 2(κ)−df 1(κ) = Tr[Σ2(Σ+κI) −2]−Tr[Σ(Σ+κI) −1] = Tr[ Σ(Σ+κI) −1 −I Σ(Σ+κI) −1] =κTr[Σ(Σ+κI) −2] >0

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.976136Z

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Observation f9b8ce05-120e-4424-b4e2-b9cf95c9f47d · outbound

This paper cites analytic continuation.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models analytic continuation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:24.092427Z

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Observation 44eb1619-d0eb-4aa4-8f4f-4b3ac21a147d · outbound

This paper cites 64 RMT of Diffusion Consistency For each data point x∈R d, the loss is computed as follows.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models 64 RMT of Diffusion Consistency For each data point x∈R d, the loss is computed as follows

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:24.237129Z

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Observation b61f27ac-16b2-4779-b405-1b6032b6cae1 · outbound

This paper cites ANISOTROPY OF INITIAL NOISE SPACE Figure 51.Anisotropic structure of the initial noise space (CNN-UNet FFHQ64).

A Random Matrix Theory Perspective on the Consistency of Diffusion Models ANISOTROPY OF INITIAL NOISE SPACE Figure 51.Anisotropic structure of the initial noise space (CNN-UNet FFHQ64)

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.907546Z

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Observation fec8b944-2d64-4a13-83eb-8b90e0a62002 · outbound

This paper cites Bonnaire, T., Urfin, R., Biroli, G., and Mézard, M.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models Bonnaire, T., Urfin, R., Biroli, G., and Mézard, M

Reference 1960

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:22.498514Z

Source-reported events for the cited work

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Observation b22b00bb-5141-4a37-9632-a9483a812a13 · outbound

This paper cites URL https: //www.mathnet.ru/eng/sm4101.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models URL https: //www.mathnet.ru/eng/sm4101

Reference 1967

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.015557Z

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Observation 09ae6301-3984-4a3d-8fa6-da9c1fcf23f2 · outbound

This paper cites A Good Score Does not Lead to A Good Generative Model.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models A Good Score Does not Lead to A Good Generative Model

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:22.937851Z

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Observation a9627f6f-4f43-46ee-baf0-e5e89c89786f · outbound

This paper cites On the Interpolation Effect of Score Smoothing in Diffusion Models.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models On the Interpolation Effect of Score Smoothing in Diffusion Models

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:22.573333Z

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Observation 350eab09-f6a7-4f0f-86bd-675113ab752a · outbound

This paper cites doi: 10.1017/9781108768900.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models doi: 10.1017/9781108768900

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.380831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29fdd2c5-fdfd-42a8-a6f4-9a995b6077c8 · outbound

This paper cites The Unreasonable Effectiveness of Gaussian Score Approximation for Diffusion Models and its Applications.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models The Unreasonable Effectiveness of Gaussian Score Approximation for Diffusion Models and its Applications

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.508374Z

Source-reported events for the cited work

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Observation 4f6825a3-9dbc-4491-a26a-f3650ad1ad2f · outbound

This paper cites Towards a Mechanistic Explanation of Diffusion Model Generalization.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models Towards a Mechanistic Explanation of Diffusion Model Generalization

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:23.078166Z

Source-reported events for the cited work

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Observation 9e8c71d6-b12b-4cf3-bd69-dabadf898239 · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:22.371198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b778e81-69ae-4cc7-a3e8-6de061d3c2a7 · outbound

This paper cites An analytic theory of creativity in convolutional diffusion models.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models An analytic theory of creativity in convolutional diffusion models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:22.711308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ff0042c-24f7-4e7d-b8cc-eda4bf4ddb4c · outbound

This paper cites George, A.

A Random Matrix Theory Perspective on the Consistency of Diffusion Models George, A

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T05:17:22.642558Z

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Pith citing papers

Observation 9a83b654-719e-469a-af4c-1c31a31023f6 · inbound

The two clocks and the innovation window: When and how generative models learn rules cites this paper.

The two clocks and the innovation window: When and how generative models learn rules A Random Matrix Theory Perspective on the Consistency of Diffusion Models

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-07-07T03:17:17.702004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 20c13a05-fc7a-487a-8cd2-b9dce7fecd1a · inbound

Memorisation, convergence and generalisation in generative models cites this paper.

Memorisation, convergence and generalisation in generative models A Random Matrix Theory Perspective on the Consistency of Diffusion Models

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:17:17.702004Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e1a65c95-8c6e-42e1-9e50-4985caa9344c · inbound

An exact information theory of generalization phase transitions in Bayesian diffusion models cites this paper.

An exact information theory of generalization phase transitions in Bayesian diffusion models A Random Matrix Theory Perspective on the Consistency of Diffusion Models

Reference 20

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T01:26:43.159544Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.