Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin | Paper Citation Record

Observation 38970deb-f4a0-4e2c-a89d-b1b2226c3779 · outbound

This paper cites Learning multiple layers of features from tiny images.https://www.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Learning multiple layers of features from tiny images.https://www

Reference 1

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Observation e6ebd8cb-08ba-416a-9bc0-7b728ab2b943 · outbound

This paper cites Springer Science & Business Media, 2008.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Springer Science & Business Media, 2008

Reference 2

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Observation 8ab5cc79-3330-4f2d-8fd4-cd9b44a6d37f · outbound

This paper cites Estimating the optimal covariance with imperfect mean in diffusion probabilistic models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Estimating the optimal covariance with imperfect mean in diffusion probabilistic models

Reference 3

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Observation c159c8af-dde6-4300-bbd0-d525e7a3e0fc · outbound

This paper cites Springer series in statistics.Principles and Theory for Data Mining and Machine Learning.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Springer series in statistics.Principles and Theory for Data Mining and Machine Learning

Reference 4

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Observation 62bdd584-bca8-444d-b67c-13cd5a4cb4fc · outbound

This paper cites Existence and uniqueness of so- lutions to fokker–planck type equations with irregular coef- ficients.Communications in Partial Differential Equations, 33(7):1272–1317, 2008.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Existence and uniqueness of so- lutions to fokker–planck type equations with irregular coef- ficients.Communications in Partial Differential Equations, 33(7):1272–1317, 2008

Reference 5

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Observation 65564a9d-ce1b-4787-a93a-2b3d92a386b6 · outbound

This paper cites A limited memory algorithm for bound constrained optimization.SIAM Journal on scientific computing, 16(5): 1190–1208, 1995.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin A limited memory algorithm for bound constrained optimization.SIAM Journal on scientific computing, 16(5): 1190–1208, 1995

Reference 6

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Observation 1e20ee71-f1b9-46b8-ad9a-42aba4a3ca36 · outbound

This paper cites On the Trajectory Regularity of ODE-based Diffusion Sampling.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin On the Trajectory Regularity of ODE-based Diffusion Sampling

Reference 7

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Observation c3e9836d-9f38-407a-ac64-f6a861dbca32 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 8

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Observation 51abefa7-f09c-45f1-b5c9-f6fae7c104b4 · outbound

This paper cites Stochastic gradient hamiltonian monte carlo.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Stochastic gradient hamiltonian monte carlo

Reference 9

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Observation 0dd1960e-a160-47ba-b5bd-6e7fac03c350 · outbound

This paper cites Dsl-fiqa: As- sessing facial image quality via dual-set degradation learn- ing and landmark-guided transformer.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Dsl-fiqa: As- sessing facial image quality via dual-set degradation learn- ing and landmark-guided transformer

Reference 10

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Observation 7df03acf-c10f-44ae-b71c-d38095d8b758 · outbound

This paper cites Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow

Reference 11

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Observation bfb4e4d7-cd71-4d42-a7e7-47ea160d2a89 · outbound

This paper cites Exponential ergod- icity of mirror-langevin diffusions.Advances in Neural In- formation Processing Systems, 33:19573–19585, 2020.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Exponential ergod- icity of mirror-langevin diffusions.Advances in Neural In- formation Processing Systems, 33:19573–19585, 2020

Reference 12

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Observation 52ca25dc-64f1-4fc9-acff-9e353c3fd8db · outbound

This paper cites Diffusion models beat gans on image synthesis.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Diffusion models beat gans on image synthesis

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:31.015129Z

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Observation f8405d27-080b-42fc-ba0b-908f176dc0ba · outbound

This paper cites A note on quadratic transportation and diver- gence inequality.Statistics & Probability Letters, 100:115– 123, 2015.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin A note on quadratic transportation and diver- gence inequality.Statistics & Probability Letters, 100:115– 123, 2015

Reference 14

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Observation af05673d-a8c7-403b-b717-a0fad97a7492 · outbound

This paper cites Genie: Higher-order denoising diffusion solvers.Advances in Neu- ral Information Processing Systems, 35:30150–30166, 2022.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Genie: Higher-order denoising diffusion solvers.Advances in Neu- ral Information Processing Systems, 35:30150–30166, 2022

Reference 15

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This paper cites Gauss-newton/levenberg-marquardt optimiza- tion.Tech.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Gauss-newton/levenberg-marquardt optimiza- tion.Tech

Reference 16

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Observation 59838012-98b9-49c6-a11e-7c5fb12af980 · outbound

This paper cites An adaptive multi-step levenberg–marquardt method.Journal of Scien- tific Computing, 78:531–548, 2019.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin An adaptive multi-step levenberg–marquardt method.Journal of Scien- tific Computing, 78:531–548, 2019

Reference 17

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Observation 566e9409-5819-44dc-b81a-4348bf0f28d2 · outbound

This paper cites PECTP: Parameter-Efficient Cross-Task Prompts for Incremental Vision Transformer.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin PECTP: Parameter-Efficient Cross-Task Prompts for Incremental Vision Transformer

Reference 18

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Observation 605be463-847d-45e3-bb4e-64cfa6817ef5 · outbound

This paper cites LW2G: Learning Whether to Grow for Prompt-based Continual Learning.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin LW2G: Learning Whether to Grow for Prompt-based Continual Learning

Reference 19

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Observation dfb718ce-d6e8-438e-bb93-49d9710c1189 · outbound

This paper cites Unit stepsize for the newton method close to critical solu- tions.Mathematical Programming, 187(1):697–721, 2021.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Unit stepsize for the newton method close to critical solu- tions.Mathematical Programming, 187(1):697–721, 2021

Reference 20

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This paper cites IAP: Improving Continual Learning of Vision-Language Models via Instance-Aware Prompting.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin IAP: Improving Continual Learning of Vision-Language Models via Instance-Aware Prompting

Reference 21

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Observation cebd3e5b-af62-4a60-a3a9-0163da2efcd1 · outbound

This paper cites Quasi - newton hamiltonian monte carlo.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Quasi - newton hamiltonian monte carlo

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:31.713760Z

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Observation 73588372-de33-4358-93fb-9cdfe09419e9 · outbound

This paper cites Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis

Reference 23

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Observation c8224055-01de-4218-a1c6-f7374f115d46 · outbound

This paper cites Hilbert-schmidt operators.Classes of Linear Op- erators Vol.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Hilbert-schmidt operators.Classes of Linear Op- erators Vol

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:52.122337Z

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Observation 81f09156-a1cf-4497-b55e-6e681080abed · outbound

This paper cites An efficient step size control for continuation methods.BIT Numerical Mathemat- ics, 20:475–485, 1980.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin An efficient step size control for continuation methods.BIT Numerical Mathemat- ics, 20:475–485, 1980

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:51.925504Z

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Observation 39241f43-0f4d-4588-8da5-0729b54ebbfd · outbound

This paper cites Measuring color- fulness in natural images.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Measuring color- fulness in natural images

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:51.720540Z

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Observation 12d05814-422a-4b94-b421-3a8835ca366a · outbound

This paper cites Eat: An enhancer for aesthetics-oriented transformers.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Eat: An enhancer for aesthetics-oriented transformers

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:51.501724Z

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Observation 45a162eb-bdef-4606-9580-e066d3e4f544 · outbound

This paper cites Neue begr ¨undung der theorie quadratis- cher formen von unendlichvielen ver ¨anderlichen.Journal f¨ur die reine und angewandte Mathematik, 1909(136):210– 271, 1909.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Neue begr ¨undung der theorie quadratis- cher formen von unendlichvielen ver ¨anderlichen.Journal f¨ur die reine und angewandte Mathematik, 1909(136):210– 271, 1909

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:51.161200Z

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Observation 074ff36f-9cf6-4e6a-8b5a-e6c324fb8b2b · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in Neural Information Processing Systems (NeurIPS), 2017.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in Neural Information Processing Systems (NeurIPS), 2017

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:50.927862Z

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Observation 8bbcfb03-3fb3-4f3a-96fd-910b86d73de8 · outbound

This paper cites Denoising diffu- sion probabilistic models.Advances in Neural Information Processing Systems, 33:6840–6851, 2020.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Denoising diffu- sion probabilistic models.Advances in Neural Information Processing Systems, 33:6840–6851, 2020

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:50.506513Z

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Observation 8867e4d9-bd07-4e29-a9b2-a8dfa5b1e6f9 · outbound

This paper cites Fleet, Mohammad Norouzi, and Tim Salimans.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Fleet, Mohammad Norouzi, and Tim Salimans

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:50.383158Z

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Observation 689e10a7-4520-45a5-9c87-4577f690bc18 · outbound

This paper cites Cambridge university press, 2012.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Cambridge university press, 2012

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:50.205219Z

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Observation 7027a412-f862-424c-8ecf-facc97100d47 · outbound

This paper cites Mirrored langevin dynamics.Advances in Neural Informa- tion Processing Systems, 31, 2018.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Mirrored langevin dynamics.Advances in Neural Informa- tion Processing Systems, 31, 2018

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:50.041157Z

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Observation c4795ea3-37ad-4373-8d30-da543ca30b3a · outbound

This paper cites T2i-compbench: A comprehensive bench- mark for open-world compositional text-to-image genera- tion.Advances in Neural Information Processing Systems, 36:78723–78747, 2023.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin T2i-compbench: A comprehensive bench- mark for open-world compositional text-to-image genera- tion.Advances in Neural Information Processing Systems, 36:78723–78747, 2023

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:49.891605Z

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Observation 4caf1232-c151-4862-a730-ebefb57e24f1 · outbound

This paper cites Gotta Go Fast When Generating Data with Score-Based Models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Gotta Go Fast When Generating Data with Score-Based Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:33.004091Z

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Observation 6a0d3de6-e27c-4d9d-bae1-cdfc4bec4606 · outbound

This paper cites The variational formulation of the fokker–planck equation.SIAM journal on mathematical analysis, 29(1):1–17, 1998.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin The variational formulation of the fokker–planck equation.SIAM journal on mathematical analysis, 29(1):1–17, 1998

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:49.575522Z

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Observation 20ef6bdd-6f6b-4164-a16f-63feb2388bc2 · outbound

This paper cites Univ of California Press, 1987.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Univ of California Press, 1987

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:49.076900Z

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Observation 8bb2f6e2-6bbc-4b09-aefd-658ee8252561 · outbound

This paper cites springer, 2014.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin springer, 2014

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:48.614403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 38b74afe-f9f7-4891-884a-e93ab2b2ed61 · outbound

This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:33.331024Z

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Observation ff4baf3a-eb3c-4aeb-a07f-9db0be495228 · outbound

This paper cites Elucidating the Design Space of Diffusion-Based Generative Models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Elucidating the Design Space of Diffusion-Based Generative Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:33.399410Z

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Observation 4099f6c4-493e-471e-94ce-ae9ef53b19d1 · outbound

This paper cites Stabilization of geometrically nonlinear topology optimization by the levenberg–marquardt method.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Stabilization of geometrically nonlinear topology optimization by the levenberg–marquardt method

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:48.348481Z

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Observation 4f26f8d8-d42a-446b-9844-2a65683f2924 · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Pick-a-pic: An open dataset of user preferences for text-to-image generation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:48.040438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cebb9a15-c003-4cc4-af0b-fba9cb5ee897 · outbound

This paper cites Dynamical newton-like methods with adaptive stepsize for solving nonlinear alge- braic equations.Computers, Materials, & Continua, 31(3): 173–200, 2012.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Dynamical newton-like methods with adaptive stepsize for solving nonlinear alge- braic equations.Computers, Materials, & Continua, 31(3): 173–200, 2012

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:47.829091Z

Source-reported events for the cited work

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Observation 82eafcc9-117c-4c89-85ad-c18f0e27979d · outbound

This paper cites On information and sufficiency.The annals of mathematical statistics, 22(1): 79–86, 1951.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin On information and sufficiency.The annals of mathematical statistics, 22(1): 79–86, 1951

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:47.643169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 500084a9-4bad-466a-904f-345e25cc8fe0 · outbound

This paper cites A method for the solution of certain non-linear problems in least squares.Quarterly of applied mathematics, 2(2):164–168, 1944.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin A method for the solution of certain non-linear problems in least squares.Quarterly of applied mathematics, 2(2):164–168, 1944

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:47.492301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 38f28807-a9ac-4f51-9474-2ca8f1800737 · outbound

This paper cites FaceScore: Benchmarking and Enhancing Face Quality in Human Generation.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin FaceScore: Benchmarking and Enhancing Face Quality in Human Generation

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:35:39.845065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e316a74b-fdd3-4737-a56d-4ea2ddec7d40 · outbound

This paper cites Microsoft coco: Common objects in context.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Microsoft coco: Common objects in context

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:33.936874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a98074a3-6651-4a25-91c1-3ccf35cd995d · outbound

This paper cites Flow Matching for Generative Modeling.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Flow Matching for Generative Modeling

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:34.005898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 702b53ad-c1fc-4fdf-9801-228a317c4e4e · outbound

This paper cites Mirror diffusion models for constrained and wa- termarked generation.Advances in Neural Information Pro- cessing Systems, 36:42898–42917, 2023.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Mirror diffusion models for constrained and wa- termarked generation.Advances in Neural Information Pro- cessing Systems, 36:42898–42917, 2023

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:47.275319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 61fe712b-35d9-45f0-828c-7b629ee14b3d · outbound

This paper cites Pseudo Numerical Methods for Diffusion Models on Manifolds.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Pseudo Numerical Methods for Diffusion Models on Manifolds

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:34.199905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3471b1f-72bd-44f8-9429-0d1f157f8f64 · outbound

This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.Advances in Neural Information Processing Systems, 35:5775–5787,.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.Advances in Neural Information Processing Systems, 35:5775–5787,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:34.318550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06386810-40dd-479f-9bec-6cec6554097f · outbound

This paper cites DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:34.409930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 217450b7-de62-4c9f-a004-d3448bb9d862 · outbound

This paper cites An algorithm for least-squares esti- mation of nonlinear parameters.Journal of the society for Industrial and Applied Mathematics, 11(2):431–441, 1963.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin An algorithm for least-squares esti- mation of nonlinear parameters.Journal of the society for Industrial and Applied Mathematics, 11(2):431–441, 1963

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:47.127642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 217d4053-0811-43d2-8356-8449732e57d5 · outbound

This paper cites A stochastic newton mcmc method for large- scale statistical inverse problems with application to seismic inversion.SIAM Journal on Scientific Computing, 34(3): A1460–A1487, 2012.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin A stochastic newton mcmc method for large- scale statistical inverse problems with application to seismic inversion.SIAM Journal on Scientific Computing, 34(3): A1460–A1487, 2012

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:46.946843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3e4d676a-ce38-4a97-ad3c-9f9eb8cc1cf8 · outbound

This paper cites Problem complexity and method efficiency in opti- mization.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Problem complexity and method efficiency in opti- mization

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:46.774911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4aab293b-ba75-44f2-b8d8-f4ae69f666fa · outbound

This paper cites Springer, 2018.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Springer, 2018

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:46.615772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e18aa7e3-68b9-4164-88b9-f2fe7e480ae8 · outbound

This paper cites Efficient training of neural nets for nonlinear adaptive filtering using a recursive levenberg-marquardt algorithm.IEEE Transactions on Sig- nal Processing, 48(7):1915–1927, 2000.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Efficient training of neural nets for nonlinear adaptive filtering using a recursive levenberg-marquardt algorithm.IEEE Transactions on Sig- nal Processing, 48(7):1915–1927, 2000

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:46.431773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 30a37f45-464f-4ca5-8ca6-3e23d8f4123b · outbound

This paper cites GLIDE: Towards photorealis- tic image generation and editing with text-guided diffusion models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin GLIDE: Towards photorealis- tic image generation and editing with text-guided diffusion models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:46.249138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1ee83010-dd3c-4daa-a291-b120a7d0c422 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:35.019602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 851be0f3-c5e2-48fa-aa1d-a40ca5fc9fe2 · outbound

This paper cites Newton’s method and its use in optimiza- tion.European Journal of Operational Research, 181(3): 1086–1096, 2007.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Newton’s method and its use in optimiza- tion.European Journal of Operational Research, 181(3): 1086–1096, 2007

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:46.064023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb5ca013-4322-420e-a7e1-7dda4f0100f6 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Learn- ing transferable visual models from natural language super- vision

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:45.869796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9555301a-1d29-41e3-ba52-2c628636d11d · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:35.501963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f8bedba-cb2e-4b03-bfca-b0f09a5166e2 · outbound

This paper cites The fokker-planck equation, 1996.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin The fokker-planck equation, 1996

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:45.709950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ddaf969d-6c40-4379-af2f-88b6309264e6 · outbound

This paper cites Free hunch: Denoiser covariance estimation for diffusion models without extra costs.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Free hunch: Denoiser covariance estimation for diffusion models without extra costs

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:45.536584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 96f9d914-1b16-4d1e-b1e8-ddc62cabb138 · outbound

This paper cites Monte carlo statistical methods, 1999.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Monte carlo statistical methods, 1999

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:45.364182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 71b71671-bf36-44f6-965b-47389354f234 · outbound

This paper cites Convex analysis:(pms-28).

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Convex analysis:(pms-28)

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:45.216579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 692a3757-9e5d-4d2a-8fb2-0196c1534a1e · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin High-resolution image synthesis with latent diffusion models

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:45.060083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ca601e1-3cc9-4327-b6e2-971dfd6ae38b · outbound

This paper cites Levenberg-marquardt optimization.Notes, University Of Toronto, 52, 1996.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Levenberg-marquardt optimization.Notes, University Of Toronto, 52, 1996

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:44.883798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f4f7031a-829c-4766-a94d-0180bf5cf689 · outbound

This paper cites Fleet, and Mohammad Norouzi.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Fleet, and Mohammad Norouzi

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:44.710194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 14da3413-940c-47e7-9359-859f1d4ed60f · outbound

This paper cites Photorealistic text-to-image diffusion models with deep lan- guage understanding.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Photorealistic text-to-image diffusion models with deep lan- guage understanding

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:44.562340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 027c1f83-a962-4880-ae73-8d8a622f2033 · outbound

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

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in neural in- formation processing systems, 35:25278–25294, 2022

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:36.823684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47ee6ef8-0ce8-4eb3-883a-785f12060554 · outbound

This paper cites Adjustment of an inverse matrix corresponding to a change in one element of a given matrix.The Annals of Mathematical Statistics, 21(1): 124–127, 1950.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Adjustment of an inverse matrix corresponding to a change in one element of a given matrix.The Annals of Mathematical Statistics, 21(1): 124–127, 1950

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:44.401501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b93e1914-41c6-4dc7-9a11-a8128b649fd9 · outbound

This paper cites Stochastic quasi-newton langevin monte carlo.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Stochastic quasi-newton langevin monte carlo

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:44.230440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9acd0dfd-fae2-41c5-950a-5d25b5959ded · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Deep unsupervised learning using nonequilibrium thermodynamics

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:44.018724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fccac182-f242-4800-80be-d9129d671579 · outbound

This paper cites Denois- ing diffusion implicit models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Denois- ing diffusion implicit models

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:43.794238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cb8fc011-1cb7-4100-bf2b-c332e9e8339f · outbound

This paper cites Generative modeling by esti- mating gradients of the data distribution.Advances in neural information processing systems, 32, 2019.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Generative modeling by esti- mating gradients of the data distribution.Advances in neural information processing systems, 32, 2019

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:43.587272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 394f7830-8310-4137-815f-6eb56f1cb27f · outbound

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

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Score-Based Generative Modeling through Stochastic Differential Equations

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.349516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e16349d7-a1d2-4eb4-a199-5bd95945735d · outbound

This paper cites Texttoucher: Fine-grained text-to- touch generation.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Texttoucher: Fine-grained text-to- touch generation

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:43.432958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 16c88b51-dacf-4a31-9b15-a170247ae199 · outbound

This paper cites Driveditfit: Fine-tuning diffusion transformers for autonomous driving data generation.ACM Transactions on Multimedia Computing, Communications and Applications, 21(3):1–29, 2025.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Driveditfit: Fine-tuning diffusion transformers for autonomous driving data generation.ACM Transactions on Multimedia Computing, Communications and Applications, 21(3):1–29, 2025

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:43.244619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4a53c747-7648-45c9-a818-3ac2255655c8 · outbound

This paper cites Total variation distance and the distribution of relative information.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Total variation distance and the distribution of relative information

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:43.032122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c952ba57-3050-4622-b1f5-f94d68fe2312 · outbound

This paper cites Springer, 2009.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Springer, 2009

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:42.846342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e4e78a0a-0171-4d1d-8853-5dac927d53a9 · outbound

This paper cites BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Models

Reference 82

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:35:39.604501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4bf2ec8a-1948-4bfa-9264-fe9a207e1870 · outbound

This paper cites Gad-pvi: A general accelerated dynamic-weight particle-based variational inference frame- work.Entropy, 26(8):679, 2024.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Gad-pvi: A general accelerated dynamic-weight particle-based variational inference frame- work.Entropy, 26(8):679, 2024

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:42.587933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f606b70f-f47b-490f-8d52-f0fac4afab78 · outbound

This paper cites Efficiently access diffusion fisher: Within the outer product span space, 2025.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Efficiently access diffusion fisher: Within the outer product span space, 2025

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:42.339131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb0f190b-0f6d-445a-af90-41b407621eac · outbound

This paper cites Bayesian learning via stochas- tic gradient langevin dynamics.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Bayesian learning via stochas- tic gradient langevin dynamics

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.140352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70ac6670-261e-4596-8d2a-8b912e0b0cd3 · outbound

This paper cites Towards more accurate diffusion model acceleration with a timestep tuner.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Towards more accurate diffusion model acceleration with a timestep tuner

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:42.182354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cd2057b3-83b9-41d8-89b4-eef33197486b · outbound

This paper cites Accelerating diffu- sion sampling with optimized time steps.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Accelerating diffu- sion sampling with optimized time steps

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:41.992573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e88f1a07-5fd3-423e-9ed4-f52217219b23 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Adding conditional control to text-to-image diffusion models

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:41.775658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 12e81702-6253-4e31-beeb-19f8a1cabc9a · outbound

This paper cites Tackling the Singularities at the Endpoints of Time Intervals in Diffusion Models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Tackling the Singularities at the Endpoints of Time Intervals in Diffusion Models

Reference 89

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:35:39.319785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cf918172-b76d-4be4-a1f5-7a5deabb5038 · outbound

This paper cites Fast Sampling of Diffusion Models with Exponential Integrator.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Fast Sampling of Diffusion Models with Exponential Integrator

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.630941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de37bbe0-0ea2-4d60-90bd-45d520dbc504 · outbound

This paper cites Unipc: A unified predictor-corrector framework for fast sampling of diffusion models.Advances in Neural Information Processing Systems, 36, 2024.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Unipc: A unified predictor-corrector framework for fast sampling of diffusion models.Advances in Neural Information Processing Systems, 36, 2024

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:41.561088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f511f900-1b79-486e-b302-0a707e6e8c24 · outbound

This paper cites Dpm- solver-v3: Improved diffusion ode solver with empirical model statistics.Advances in Neural Information Process- ing Systems, 36:55502–55542, 2023.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Dpm- solver-v3: Improved diffusion ode solver with empirical model statistics.Advances in Neural Information Process- ing Systems, 36:55502–55542, 2023

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:41.297824Z

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Observation 3bc0349e-f5ea-466c-a6bb-08546c34e90c · outbound

This paper cites Fast ode-based sampling for diffusion models in around 5 steps.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Fast ode-based sampling for diffusion models in around 5 steps

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.902339Z

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Observation 700a781c-eb1e-416e-a390-76c914f2a29f · outbound

This paper cites Analyzing and Mitigating Model Collapse in Rectified Flow Models.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Analyzing and Mitigating Model Collapse in Rectified Flow Models

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.976215Z

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Observation ae254d3c-08af-44a4-8349-262f029101e0 · outbound

This paper cites Neural Sinkhorn Gradient Flow.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin Neural Sinkhorn Gradient Flow

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.048047Z

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Observation 4e5de53c-b9aa-40d5-b601-7b9187526090 · outbound

This paper cites 18, we obtain the LM annealing SDE in Eq.

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin 18, we obtain the LM annealing SDE in Eq

Reference 96

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T12:35:41.083111Z

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