Paper Citation Record · LEDGER

Beyond and Free from Diffusion: Invertible Guided Consistency Training

As of 9 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2502.05391.

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

pith.paper-citation-record.v1
2502.05391 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:41:03.472871Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T18:22:57.207456Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T00:41:06.204921Z

Reference resolution

51 of 51 outbound references displayed

verified exact0
verified fuzzy6
unresolved45
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External citation measurements

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Outbound references

Observation 387ae13b-74b6-45a5-8426-a6cfecbb53ef · outbound

This paper cites Towards Principled Methods for Training Generative Adversarial Networks.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Towards Principled Methods for Training Generative Adversarial Networks

Reference 1

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Observation a41b6c1d-d8c7-4eec-993d-7c2f45e6549f · outbound

This paper cites MaskSketch: Unpaired Structure-guided Masked Image Generation.

Beyond and Free from Diffusion: Invertible Guided Consistency Training MaskSketch: Unpaired Structure-guided Masked Image Generation

Reference 5

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Observation 8fb277ae-4192-4a05-9285-720d6fba8a5b · outbound

This paper cites A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets.

Beyond and Free from Diffusion: Invertible Guided Consistency Training A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets

Reference 8

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Observation fd08b9bb-a2b8-4af0-a901-078292b1f73f · outbound

This paper cites Dong, W., Xue, S., Duan, X., and Han, S.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Dong, W., Xue, S., Duan, X., and Han, S

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:41:04.288439Z

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Observation 5f0b07db-6bb7-4b9c-ba74-1f5937539be1 · outbound

This paper cites ReNoise: Real Image Inversion Through Iterative Noising.

Beyond and Free from Diffusion: Invertible Guided Consistency Training ReNoise: Real Image Inversion Through Iterative Noising

Reference 11

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Observation 4696b4fa-cadb-4097-9045-003208f10571 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Classifier-Free Diffusion Guidance

Reference 14

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Observation e80c3daf-36fe-450c-9297-87b2ef5da34e · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Imagen Video: High Definition Video Generation with Diffusion Models

Reference 16

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Observation d442df79-6fd4-489a-a527-6b36bbafe02d · outbound

This paper cites Efficient Text-driven Motion Generation via Latent Consistency Training.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Efficient Text-driven Motion Generation via Latent Consistency Training

Reference 17

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Observation 2a46e7fb-45a0-44f8-a274-6ddea8d0f778 · outbound

This paper cites Composer: Creative and Controllable Image Synthesis with Composable Conditions.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Composer: Creative and Controllable Image Synthesis with Composable Conditions

Reference 18

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Observation bd35315b-e4a8-4262-ab0e-5fbfef7cefae · outbound

This paper cites A Style-Based Generator Architecture for Generative Adversarial Networks.

Beyond and Free from Diffusion: Invertible Guided Consistency Training A Style-Based Generator Architecture for Generative Adversarial Networks

Reference 19

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Observation 7d3febca-dd67-4ff5-9ea7-10e233f8b567 · outbound

This paper cites Training Generative Adversarial Networks with Limited Data.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Training Generative Adversarial Networks with Limited Data

Reference 20

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Observation 375c4e36-6af6-41ff-913d-dc093503172a · outbound

This paper cites Guiding a Diffusion Model with a Bad Version of Itself.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Guiding a Diffusion Model with a Bad Version of Itself

Reference 21

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Observation e2231ca0-198f-4672-ab51-f3ba2cfa007c · outbound

This paper cites Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion

Reference 23

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Observation 3cedfcb9-dbb5-4377-a19e-39910ea3fdc8 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Adam: A Method for Stochastic Optimization

Reference 24

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Observation 60a751ca-21cd-4631-8fb0-f05722fbd971 · outbound

This paper cites Improved Precision and Recall Metric for Assessing Generative Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Improved Precision and Recall Metric for Assessing Generative Models

Reference 26

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Observation b6e53830-0559-4f2a-a955-c1c57c827958 · outbound

This paper cites Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models

Reference 27

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Observation 806b4e53-1884-400a-a771-05b6a727a79a · outbound

This paper cites StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing.

Beyond and Free from Diffusion: Invertible Guided Consistency Training StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing

Reference 29

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Observation c137422f-245f-4906-9c59-e3776ab4ec30 · outbound

This paper cites Magic3D: High-Resolution Text-to-3D Content Creation.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Magic3D: High-Resolution Text-to-3D Content Creation

Reference 30

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Observation 9c6f410e-2abe-44be-a43d-3fbfd55a1855 · outbound

This paper cites Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models

Reference 31

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Observation 09a90880-a29e-4094-8be7-480869cbc05b · outbound

This paper cites DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps.

Beyond and Free from Diffusion: Invertible Guided Consistency Training DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps

Reference 32

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Observation 62779c76-1404-4604-93fa-6a866decbe9c · outbound

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

Beyond and Free from Diffusion: Invertible Guided Consistency Training DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.383581Z

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Observation a6b62130-6b1f-4b20-8260-ff1eb96fbb71 · outbound

This paper cites SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.

Beyond and Free from Diffusion: Invertible Guided Consistency Training SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations

Reference 34

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Observation c62d3ef1-d707-4cfd-8ff7-0c9ed1b670d4 · outbound

This paper cites Unrolled Generative Adversarial Networks.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Unrolled Generative Adversarial Networks

Reference 35

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Observation eafe39f7-d59a-47c5-ab42-20c345b2e204 · outbound

This paper cites Improved Denoising Diffusion Probabilistic Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Improved Denoising Diffusion Probabilistic Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.403291Z

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Observation cd41ff98-2e19-4dc4-8832-fa1c568002be · outbound

This paper cites $\textit{Jump Your Steps}$: Optimizing Sampling Schedule of Discrete Diffusion Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training $\textit{Jump Your Steps}$: Optimizing Sampling Schedule of Discrete Diffusion Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.407857Z

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Observation a0c33685-2562-45f5-bc58-22aa85784b0a · outbound

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

Beyond and Free from Diffusion: Invertible Guided Consistency Training SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.412369Z

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Observation 763850e2-e91c-4676-a628-11321a3567f6 · outbound

This paper cites Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

Reference 40

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Observation 5f7b105a-47b0-485a-9593-e6f61fa2a3b8 · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Progressive Distillation for Fast Sampling of Diffusion Models

Reference 41

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Observation 114adf28-be60-4291-85c3-bdf76330c04a · outbound

This paper cites Denoising Diffusion Implicit Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Denoising Diffusion Implicit Models

Reference 42

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Observation cfdb94fe-8c1c-4888-a77d-4e1b24885e9b · outbound

This paper cites Generative Modeling by Estimating Gradients of the Data Distribution.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Generative Modeling by Estimating Gradients of the Data Distribution

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.430512Z

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Observation 9b25cbda-41dc-49fd-9b87-a69606491c2d · outbound

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

Beyond and Free from Diffusion: Invertible Guided Consistency Training Score-Based Generative Modeling through Stochastic Differential Equations

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.435449Z

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Observation 45c0ae33-4181-4dc1-a9c2-f3240b59e875 · outbound

This paper cites Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.440325Z

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Observation 81f09aad-2e4a-4efd-968a-69a9bed8b9c1 · outbound

This paper cites Image Data Augmentation for Deep Learning: A Survey.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Image Data Augmentation for Deep Learning: A Survey

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.444913Z

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Observation f196c307-10e6-4c21-9158-2faafecf122f · outbound

This paper cites Adding Conditional Control to Text-to-Image Diffusion Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Adding Conditional Control to Text-to-Image Diffusion Models

Reference 47

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Observation c0348869-c366-4b13-9f49-b93c94a0310d · outbound

This paper cites First, we present the pseudocode for the key components of iGCT.

Beyond and Free from Diffusion: Invertible Guided Consistency Training First, we present the pseudocode for the key components of iGCT

Reference 48

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Observation 20ebe631-fb3d-4af9-a61c-e8ec5f8f2811 · outbound

This paper cites an unresolved cited work.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Unresolved cited work

Reference 49

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Observation afcae00f-9e5f-4458-9a03-cd8b6e64b776 · outbound

This paper cites For ImageNet64, iGCT employs a reduced ADM architecture (Dhariwal & Nichol,.

Beyond and Free from Diffusion: Invertible Guided Consistency Training For ImageNet64, iGCT employs a reduced ADM architecture (Dhariwal & Nichol,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:41:04.245070Z

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Observation 0ceaf50d-f757-4f7e-a9d6-5a25dc367a74 · outbound

This paper cites A higher dropout rate and Pseudo-Huber loss with c = 0.06 is used, following prior works (Geng et al., 2024; Song & Dhariwal, 2023).

Beyond and Free from Diffusion: Invertible Guided Consistency Training A higher dropout rate and Pseudo-Huber loss with c = 0.06 is used, following prior works (Geng et al., 2024; Song & Dhariwal, 2023)

Reference 51

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Observation 3669dbbe-d72f-47e6-a493-a7f93c9e0d78 · outbound

This paper cites All models are trained for 250 epochs, with batch size 64, using an Adam optimizer (Kingma & Ba, 2017).

Beyond and Free from Diffusion: Invertible Guided Consistency Training All models are trained for 250 epochs, with batch size 64, using an Adam optimizer (Kingma & Ba, 2017)

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:41:04.215929Z

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Observation 81de8dab-2556-47fa-8816-b43e2a269c4c · outbound

This paper cites Generative Adversarial Networks.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Generative Adversarial Networks

Reference 2014

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Observation 20d21f67-4640-4682-b36d-c13fec4b3860 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Deep Residual Learning for Image Recognition

Reference 2015

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Observation 8bb41a7d-e987-454e-860f-f7fa76ea677b · outbound

This paper cites Negative-prompt Inversion: Fast Image Inversion for Editing with Text-guided Diffusion Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Negative-prompt Inversion: Fast Image Inversion for Editing with Text-guided Diffusion Models

Reference 2016

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Observation a5ad8546-398b-41e4-81c1-22b3a04a5d8e · outbound

This paper cites Blended diffusion for text-driven editing of natural images.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Blended diffusion for text-driven editing of natural images

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T19:41:04.303856Z

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Observation c57f399d-aba6-4bb5-8f86-f4db647ebe1c · outbound

This paper cites Generalized Consistency Trajectory Models for Image Manipulation.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Generalized Consistency Trajectory Models for Image Manipulation

Reference 2018

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Observation 76225eba-f928-458d-9364-2608e4d514b1 · outbound

This paper cites Large Scale GAN Training for High Fidelity Natural Image Synthesis.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.263020Z

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Observation 7735042f-e4ea-4011-b816-2bca5ae27097 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Denoising Diffusion Probabilistic Models

Reference 2020

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Observation 2d213836-0809-4186-bab1-6db98c8ee093 · outbound

This paper cites Diffusion Models Beat GANs on Image Synthesis.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Diffusion Models Beat GANs on Image Synthesis

Reference 2021

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Observation f2603590-f501-4e0d-8645-30dfba1cf4e8 · outbound

This paper cites URL http://dx.

Beyond and Free from Diffusion: Invertible Guided Consistency Training URL http://dx

Reference 2022

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This paper cites MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation.

Beyond and Free from Diffusion: Invertible Guided Consistency Training MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation

Reference 2023

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This paper cites Classifier-Free Guidance is a Predictor-Corrector.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Classifier-Free Guidance is a Predictor-Corrector

Reference 2024

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Observation 8561b843-4f50-455e-ad61-edfa58915c54 · outbound

This paper cites Truncated Consistency Models.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Truncated Consistency Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.360885Z

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Pith citing papers

Observation febdfafe-957a-4b21-884f-4ecb3bc50f8a · inbound

Post-Hoc Guidance for Consistency Models by Joint Flow Distribution Learning cites this paper.

Post-Hoc Guidance for Consistency Models by Joint Flow Distribution Learning Beyond and Free from Diffusion: Invertible Guided Consistency Training

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:41:06.212048Z

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