Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T18:44:21.625536Z
Paper Citation Record · LEDGER
As of 17 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 5 inbound Pith citation observations for arXiv:2506.19559.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T18:44:21.625536Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:54:29.354919Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T00:37:54.079419Z
33 of 33 outbound references displayed
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Observation 6141e2ef-6b94-49cd-af07-e3db32af37c1 · outbound
Regularity of the score function in generative models Anderson
Reference 1
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Observation 5b40918f-7a39-4f3f-b084-31ee1acf9cca · outbound
Regularity of the score function in generative models Error Bounds for Flow Matching Methods
Reference 2
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Observation c881b501-0f01-436f-9115-721b71629deb · outbound
Regularity of the score function in generative models On extensions of the brunn-minkowski and prékopa-leindler theorems, including inequalities for log concave functions, and with an application to the diffusion equation
Reference 3
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Observation 5325610d-7e22-490a-93ae-5223d6ab6666 · outbound
Regularity of the score function in generative models Heat flow, log-concavity, and Lipschitz transport maps
Reference 4
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Observation 6c874e34-d16e-4e0d-9c59-08d19199cbdc · outbound
Regularity of the score function in generative models Improved analysis of score-based generative modeling: User-friendly bounds under minimal smoothness assumptions
Reference 5
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Observation bc9102c9-e88f-45d8-9e2a-af7931a01309 · outbound
Regularity of the score function in generative models Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
Reference 6
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Observation fd005e02-7c0b-4c2f-b075-88758f8d457f · outbound
Regularity of the score function in generative models The probability flow ode is provably fast
Reference 7
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Observation 4d907b2b-4afa-47ef-add6-4a9d7314f7f2 · outbound
Regularity of the score function in generative models A coupling approach to Lipschitz transport maps
Reference 8
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Observation 8f760bc6-9bec-4802-ad06-bb3a0f84fcef · outbound
Regularity of the score function in generative models On the approximation of functions by tanh neural networks
Reference 9
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Observation 5d796e1e-79f4-4e36-b31f-c3827ffe5044 · outbound
Regularity of the score function in generative models Diffusion models beat gans on image synthesis
Reference 10
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Observation a68287ee-660f-4f9a-a995-37c8e42013f3 · outbound
Regularity of the score function in generative models Some gronwall type inequalities and applications
Reference 11
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Observation 97f93c82-1ef3-4083-ad44-e8c581471450 · outbound
Regularity of the score function in generative models Transportation onto log-lipschitz perturbations
Reference 12
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Observation 4964e47b-8871-49dd-be43-9ff21af4ab64 · outbound
Regularity of the score function in generative models Flow matching achieves almost minimax optimal convergence
Reference 13
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Observation 001c204e-2b70-4080-abf3-e01e3e25b4ac · outbound
Regularity of the score function in generative models Beyond log-concavity and score regularity: Improved convergence bounds for score-based generative models in w2-distance
Reference 14
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Observation 7ae1cf08-57ee-4964-83c9-557cedb069d6 · outbound
Regularity of the score function in generative models Equivariant diffusion for molecule generation in 3d
Reference 15
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Observation 05b372de-786c-4222-a959-1fabce4cdb9f · outbound
Regularity of the score function in generative models Convergence Analysis of Probability Flow ODE for Score-based Generative Models
Reference 16
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Observation 551a953d-b384-4e78-97d2-76c27e517512 · outbound
Regularity of the score function in generative models Elucidating the design space of diffusion-based generative models
Reference 17
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Observation 1864be32-63cc-41c4-8b40-c3f352ae818c · outbound
Regularity of the score function in generative models A generalization of caffarelli’s contraction theorem via (reverse) heat flow
Reference 18
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Observation 78e71d85-07da-46e7-b2fd-34985d392223 · outbound
Regularity of the score function in generative models DiffWave: A Versatile Diffusion Model for Audio Synthesis
Reference 19
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Observation 84864842-4262-4eed-a7ce-37c65ec5bf90 · outbound
Regularity of the score function in generative models Score-based generative modeling secretly minimizes the wasserstein distance
Reference 20
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Observation 540f8164-39d3-497a-9ac5-203e810adca8 · outbound
Regularity of the score function in generative models Convergence of score-based generative modeling for general data distributions
Reference 21
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Observation 49aabb20-633f-42aa-91c1-5ce4a113ec07 · outbound
Regularity of the score function in generative models Transport equations and flows with one-sided lipschitz velocity fields
Reference 22
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Observation 30408812-9503-4461-8661-1b6087a65862 · outbound
Regularity of the score function in generative models A bakry- \'e mery approach to lipschitz transportation on manifolds
Reference 23
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Observation c0d094f7-1a76-4c02-a950-da3e8da4e9e5 · outbound
Regularity of the score function in generative models On the lipschitz properties of transportation along heat flows
Reference 24
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Observation 3abac536-1603-4291-b422-1d0f4e11c63e · outbound
Regularity of the score function in generative models Diffusion models are minimax optimal distribution estimators
Reference 25
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Observation 9c99b13b-bb2b-42f3-b802-b8bf5f110fd5 · outbound
Regularity of the score function in generative models Improved Convergence of Score-Based Diffusion Models via Prediction-Correction
Reference 26
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Observation 28ab5f44-10a7-436c-b101-a0d7893ed228 · outbound
Regularity of the score function in generative models Nonparametric regression using deep neural networks with relu activation function
Reference 27
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Observation 13b5548a-a2f8-430d-a712-34f9d396090a · outbound
Regularity of the score function in generative models Score-Based Generative Modeling through Stochastic Differential Equations
Reference 28
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Observation c8bda7a6-8d7b-4e61-a809-70dc295fae67 · outbound
Regularity of the score function in generative models Smooth transport map via diffusion process
Reference 29
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Observation 57eeba25-7920-415a-8b3e-bb3cd0b22925 · outbound
Regularity of the score function in generative models Adaptivity of deep relu network for learning in besov and mixed smooth besov spaces: optimal rate and curse of dimensionality, 2018
Reference 30
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Observation 7123bb8e-ecaa-470e-b6e5-4726d13e3471 · outbound
Regularity of the score function in generative models Tsybakov
Reference 31
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Observation 06fb904a-c73a-40af-9892-e4fe52b98981 · outbound
Regularity of the score function in generative models Optimal transport: old and new, volume 338
Reference 32
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Observation cc056b68-3b4b-44e9-882f-5480e47eee6f · outbound
Regularity of the score function in generative models Optimal score estimation via empirical bayes smoothing
Reference 33
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Observation 1119d330-272e-46a3-9f7d-2419465325fc · inbound
Generalization bounds for score-based generative models: a synthetic proof Regularity of the score function in generative models
Reference 16
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Observation 3401b0e1-30ee-482e-a873-7ff26fde6634 · inbound
Lipschitz regularity in Flow Matching and Diffusion Models: sharp sampling rates and functional inequalities Regularity of the score function in generative models
Reference 17
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Observation 5dba0dbc-6f08-4a46-8270-3211f08edafe · inbound
Expressivity of Bi-Lipschitz Normalizing Flows: A Score-Based Diffusion Perspective Regularity of the score function in generative models
Reference 45
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Observation 299392bd-81f9-4269-ac54-aeb8d7ee8e4f · inbound
Wasserstein bounds for denoising diffusion probabilistic models via the F\"ollmer process Regularity of the score function in generative models
Reference 60
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Observation 304a4b05-72d0-4c66-851f-46caf6aa0909 · inbound
Mimicking diffusion processes with differential equations Regularity of the score function in generative models
Reference 32
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