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Paper Citation Record · LEDGER

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models

As of 9 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2602.02685.

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

pith.paper-citation-record.v1
2602.02685 v3

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:23:15.085024Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T22:46:36.367934Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T22:54:01.325706Z

Reference resolution

31 of 31 outbound references displayed

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Outbound references

Observation 16321eb0-e82b-4e83-a854-6827fa83c11e · outbound

This paper cites Diff-MoE: Diffusion transformerwithtime-awareandspace-adaptiveexperts.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Diff-MoE: Diffusion transformerwithtime-awareandspace-adaptiveexperts

Reference 1

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source=pdf_text observed=2026-08-03T05:23:11.746625Z digest=sha256:99c1a7f696e5ecf890d4db44415be326f582713487ff09083f049d7223826842

Observation 9bfbc820-ee54-4bf0-829b-62c547d29958 · outbound

This paper cites A., Levinson, N., and Teichmann, T.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models A., Levinson, N., and Teichmann, T

Reference 2

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source=pdf_text observed=2026-08-03T05:23:11.877434Z digest=sha256:e92b8470b79266110893deeddc50ced64ec4ea1ffe1c02a7f6a724269190752b

Observation de639413-c480-4c91-98cd-b5d4a8893619 · outbound

This paper cites StableMoE: Stable Routing Strategy for Mixture of Experts.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models StableMoE: Stable Routing Strategy for Mixture of Experts

Reference 3

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source=pdf_text observed=2026-08-03T05:23:11.988438Z digest=sha256:05da6e1ebd425ca27bb7c7ed27d69a6eca84fc2925eb4aeaf5d9cf28785852b4

Observation a9e17225-13db-4e3d-bf24-5f85fdc4c564 · outbound

This paper cites Efficient and accurate estimation of lipschitz constants for deep neural networks.Advances in neural information processing systems, 32, 2019.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Efficient and accurate estimation of lipschitz constants for deep neural networks.Advances in neural information processing systems, 32, 2019

Reference 4

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source=pdf_text observed=2026-08-03T05:23:12.111151Z digest=sha256:dd5c83e929169e477dc4632a6fc726a88d0c89a574462f642b44d691d386113b

Observation 51452248-96c9-4bc2-b95e-4211cd843cd1 · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022

Reference 5

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source=pdf_text observed=2026-08-03T05:23:12.240991Z digest=sha256:247951a1978ed1e828e0195762511a3a85e65dbdf7f48c45517ee1d47c1b9e50

Observation 13d40263-7642-4b4a-9034-658017713c9f · outbound

This paper cites Scaling Diffusion Transformers to 16 Billion Parameters.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Scaling Diffusion Transformers to 16 Billion Parameters

Reference 6

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source=pdf_text observed=2026-08-03T05:23:12.364687Z digest=sha256:bd45e41bd0822d510bbdf392b2cc405b1969f93a9cbd60c2beb701d97baa1fa4

Observation df79c7fe-8e99-4e77-9085-468a2ccb7f28 · outbound

This paper cites P.Solving ordinary differential equations I: Nonstiff problems.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models P.Solving ordinary differential equations I: Nonstiff problems

Reference 7

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source=pdf_text observed=2026-08-03T05:23:12.472628Z digest=sha256:b6b7eb492055c55db1bb29e870b18715e3005372a24d5a260ca00943da4cd174

Observation 34ebbe09-e702-4e9e-b402-2aafe3ddab39 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30, 2017.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30, 2017

Reference 8

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Observation a21c1785-3a26-4a64-8855-942d3aaa4383 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Classifier-Free Diffusion Guidance

Reference 9

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source=pdf_text observed=2026-08-03T05:23:12.598391Z digest=sha256:eeed62315494d4c75acd0e1349746a848c151dc73fb969185127771027babfe8

Observation 6f88005e-48b3-4591-b55d-59d43cdb81cc · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 10

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Observation 326aa4a1-8bed-479c-a1ed-5b70fd028b49 · outbound

This paper cites Paris: A Decentralized Trained Open-Weight Diffusion Model.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Paris: A Decentralized Trained Open-Weight Diffusion Model

Reference 11

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Observation 568daa2f-e38f-4ef6-8dd6-8609f6d2a52f · outbound

This paper cites and Dimakis, A.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models and Dimakis, A

Reference 12

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source=pdf_text observed=2026-08-03T05:23:12.916860Z digest=sha256:e167b4d7fb5c4a5a276b11c71399b4deecf9f41209333eed4ef23fe1fe13ca8c

Observation 2ccce7a2-45c8-4863-8289-fed2e41ceab3 · outbound

This paper cites Elucidating the design space of diffusion-based generative models.Advances in neural information processing systems, 35:26565–26577, 2022.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Elucidating the design space of diffusion-based generative models.Advances in neural information processing systems, 35:26565–26577, 2022

Reference 13

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Observation 55b2b3d3-cebe-44cb-9cac-f051b05973ad · outbound

This paper cites K., Zaheer, M., Sanjabi, M., Talwalkar, A., and Smith, V.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models K., Zaheer, M., Sanjabi, M., Talwalkar, A., and Smith, V

Reference 14

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source=pdf_text observed=2026-08-03T05:23:13.132398Z digest=sha256:0d3dc4ca7d522a20883e4ff3c7085452f32c3ed271df07fcec0750a70c418d63

Observation 6ba6bb75-e26e-4561-99b7-6ae00a8b59f5 · outbound

This paper cites Flow Matching for Generative Modeling.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Flow Matching for Generative Modeling

Reference 15

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source=pdf_text observed=2026-08-03T05:23:13.248163Z digest=sha256:b64d75c10a63fd4f05e35c4c5a64bff91a120af8b5708dfcaa94b5ff79c47547

Observation 22b43a3d-73cb-413e-a705-07fbdd49f066 · outbound

This paper cites Efficient training of diffusion mixture-of-experts models: A practical recipe.arXiv preprint arXiv:2512.01252, 2025.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Efficient training of diffusion mixture-of-experts models: A practical recipe.arXiv preprint arXiv:2512.01252, 2025

Reference 16

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source=pdf_text observed=2026-08-03T05:23:13.350098Z digest=sha256:b997f7c0db562fda4003ea250672d7acf704e037e7a0895c031548a2b8172c96

Observation 9b8f4271-5073-4cfc-aeda-cc7c133a7b88 · outbound

This paper cites Decentralized diffusion models.Proceed- ings of the Computer Vision and Pattern Recognition Conference, pp.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Decentralized diffusion models.Proceed- ings of the Computer Vision and Pattern Recognition Conference, pp

Reference 17

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source=pdf_text observed=2026-08-03T05:23:13.453130Z digest=sha256:3c23d3bd686022c9ce1b93acb6c3fbabd6a5b6d0b51788068e19a6982d5c48a7

Observation c0ff97a1-234f-452f-b445-3fb15709221f · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models DINOv2: Learning Robust Visual Features without Supervision

Reference 18

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source=pdf_text observed=2026-08-03T05:23:13.522313Z digest=sha256:88be8245d4ce2dfecfadde55ebba925e249a17fde86553eb99c3bfbf610107c8

Observation 5f1df4a1-25c5-4bf2-b396-59cfa3399870 · outbound

This paper cites and Xie, S.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models and Xie, S

Reference 19

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source=pdf_text observed=2026-08-03T05:23:13.621007Z digest=sha256:2bae9e97029fc3e62c9a6159f1aee3866bd691125576cb7806c445490c298329

Observation 2489c69d-fcd4-41ca-afef-3d27d653437e · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in neural information processing systems, 35: 25278–25294, 2022.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in neural information processing systems, 35: 25278–25294, 2022

Reference 20

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source=pdf_text observed=2026-08-03T05:23:13.741071Z digest=sha256:58e780ecb880608b516a098cafd6221b64bcfef1a011ca862803c9f38a80a821

Observation ce92ed19-a708-400a-b4a4-966871d617f9 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 21

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Observation 507dda89-2edd-45ed-83ea-d018ff14c706 · outbound

This paper cites DiffMoE: Dynamic Token Selection for Scalable Diffusion Transformers.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models DiffMoE: Dynamic Token Selection for Scalable Diffusion Transformers

Reference 22

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Observation 84bee5da-76ed-4a51-abd5-4291f9aa540b · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 23

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Observation 0908f43c-c5cb-4d8f-b0c3-76dde563e2ef · outbound

This paper cites EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing

Reference 24

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Observation ecc05f40-3333-47a2-8660-39d283aad941 · outbound

This paper cites L., and Ryu, E.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models L., and Ryu, E

Reference 25

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Observation 3f97dcc0-1ed6-47a2-a190-46a7637da123 · outbound

This paper cites and Scaman, K.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models and Scaman, K

Reference 26

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source=pdf_text observed=2026-08-03T05:23:14.534622Z digest=sha256:ec844127b0670905f4bb4ae602e0803d8ab3d6a9516a5151f7157a232f04c87b

Observation 558a8eb3-5ff3-488f-8de8-bbe90da7b3de · outbound

This paper cites Lipschitz singularities in diffusion models.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Lipschitz singularities in diffusion models

Reference 27

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source=pdf_text observed=2026-08-03T05:23:14.696352Z digest=sha256:7c5bce95fd162641b746efeaf8df731e0c47de21735c41d31064e001389dd7e8

Observation e30d2141-e45a-462f-ba1a-237d9c7685cd · outbound

This paper cites Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts

Reference 28

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source=pdf_text observed=2026-08-03T05:23:14.814561Z digest=sha256:7b510ce96b45cd5fe99ca4766fd331c081d691fb42389a7b621c1efaeee36d82

Observation af4de75d-9d36-496f-8f7c-d76335342501 · outbound

This paper cites A., Shechtman, E., and Wang, O.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models A., Shechtman, E., and Wang, O

Reference 29

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Observation 0337679b-c8fd-427c-8e94-2f0c0c4e6afe · outbound

This paper cites Dense2MoE: Restructuring diffusion transformer to moe for efficient text-to-image generation.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Dense2MoE: Restructuring diffusion transformer to moe for efficient text-to-image generation

Reference 30

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Observation 935a6a7f-45ca-46e9-b275-7523c317d43b · outbound

This paper cites M., Le, Q.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models M., Le, Q

Reference 31

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Pith citing papers

Observation c56a2b16-5a49-44a4-b398-112ade3d8f41 · inbound

Paris 2.0: A Decentralized Diffusion Model for Video Generation cites this paper.

Paris 2.0: A Decentralized Diffusion Model for Video Generation Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models

Reference 8

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source=pdf_text observed=2026-06-29T22:46:36.367934Z digest=sha256:ddb6ea13b6f0de5ad8b6c6e414353a3c286aa001d6d23ba49beff2e58f45d560