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Paper Citation Record · LEDGER

TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2303.04248.

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

pith.paper-citation-record.v1
2303.04248 v1

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measured 0 of 0 reference resolution

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measured 32 of 32 standing notices

One-hop event checks from named stored sources.

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

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:18:03.721991Z

measured 0 of 1 external citation measurements

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Source: arxiv_reference, observed 2026-07-03T22:18:59.564338Z

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Outbound references

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Pith citing papers

Observation eff2431b-ed2c-4603-970a-8711e6c78bf9 · inbound

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

SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2

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arxiv_id, observed 2026-05-10T15:22:03.555006Z

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

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Observation 5ad19db8-5cf2-45fd-8fe7-e315be5f5863 · inbound

Improved Techniques for Training Consistency Models cites this paper.

Improved Techniques for Training Consistency Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 1

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arxiv_id, observed 2026-05-21T05:04:10.617550Z

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

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Observation 5971fca8-fd46-42cc-9d4d-25d50048a655 · inbound

One Step Diffusion via Shortcut Models cites this paper.

One Step Diffusion via Shortcut Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2

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arxiv_id, observed 2026-05-15T06:40:55.430483Z

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

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Observation 3eeca111-03a6-4be1-8932-9897bfd8d448 · inbound

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples cites this paper.

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 1

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source=pdf_text observed=2026-08-12T21:18:03.721991Z digest=sha256:8da1cde286e634936c7e9e0f5e548ac149889b67a54f465820fef29ddf79585a

Observation d95e9927-7e9a-4602-b77f-11b91d30b204 · inbound

Adversarial Diffusion Compression for Real-World Image Super-Resolution cites this paper.

Adversarial Diffusion Compression for Real-World Image Super-Resolution TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2

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Observation ac007b57-9c7c-494f-81f2-2b119226ea46 · inbound

Panoptic Diffusion Models: co-generation of images and segmentation maps cites this paper.

Panoptic Diffusion Models: co-generation of images and segmentation maps TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 5

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source=arxiv_source observed=2026-08-11T23:02:16.046098Z digest=sha256:8be5911b69df4d7dec1048ebad1b434a707bca8f450abbb91602be36aa93a4b8

Observation 343fce50-3d3e-45f5-a435-44b5c15a1ae5 · inbound

Inference-Time Diffusion Model Distillation cites this paper.

Inference-Time Diffusion Model Distillation TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2

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Observation e4ba8af4-eaf7-4249-ad34-d7c94ee20885 · inbound

An Ordinary Differential Equation Sampler with Stochastic Start for Diffusion Bridge Models cites this paper.

An Ordinary Differential Equation Sampler with Stochastic Start for Diffusion Bridge Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 19

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Observation 3bcb503f-b8e6-4fcc-86c5-6d4038580b21 · inbound

PQD: Post-training Quantization for Efficient Diffusion Models cites this paper.

PQD: Post-training Quantization for Efficient Diffusion Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 3

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Observation f552b731-c426-4de9-84ee-db2b87995a90 · inbound

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models cites this paper.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2023

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Observation 20eea859-bf0c-4bcb-a170-03f4bd435fd4 · inbound

Masked Generative Nested Transformers with Decode Time Scaling cites this paper.

Masked Generative Nested Transformers with Decode Time Scaling TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2023

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Observation b935c1fb-1327-417f-aef3-d5e7c4d1b04b · inbound

Improved Training Technique for Latent Consistency Models cites this paper.

Improved Training Technique for Latent Consistency Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2019

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Observation 64bf92dd-92d6-46bc-9411-26bf3fc498f9 · inbound

A Survey on Pre-Trained Diffusion Model Distillations cites this paper.

A Survey on Pre-Trained Diffusion Model Distillations TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 4

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Observation 78ce272a-c56e-478a-8cda-21e52796ae82 · inbound

Score-of-Mixture Training: Training One-Step Generative Models Made Simple via Score Estimation of Mixture Distributions cites this paper.

Score-of-Mixture Training: Training One-Step Generative Models Made Simple via Score Estimation of Mixture Distributions TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2017

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Observation 41f002e9-edf5-4c97-b344-b5f0e2dd1bf8 · inbound

Toward Theoretical Insights into Diffusion Trajectory Distillation via Operator Merging cites this paper.

Toward Theoretical Insights into Diffusion Trajectory Distillation via Operator Merging TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 1

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arxiv_id, observed 2026-05-22T13:26:35.776328Z

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

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Observation 98e767a4-1908-48f0-9ec6-5fd9b18c5777 · inbound

Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation cites this paper.

Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 5

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Observation 1ca1f217-a8b9-47ad-ba5b-c1e294e27969 · inbound

Dual-Expert Consistency Model for Efficient and High-Quality Video Generation cites this paper.

Dual-Expert Consistency Model for Efficient and High-Quality Video Generation TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 1

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Observation 28d8f713-ed57-4d39-9ba2-5158158d729b · inbound

DiffPR: Diffusion-Based Phase Reconstruction via Frequency-Decoupled Learning cites this paper.

DiffPR: Diffusion-Based Phase Reconstruction via Frequency-Decoupled Learning TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 1982

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Observation ee012796-7f9d-4ddd-9af9-48cd1a16939f · inbound

CoVAE: Consistency Training of Variational Autoencoders cites this paper.

CoVAE: Consistency Training of Variational Autoencoders TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 8

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Observation a4f25963-5e60-4ac3-b05d-8ecbb7e5f783 · inbound

Distilling Parallel Gradients for Fast ODE Solvers of Diffusion Models cites this paper.

Distilling Parallel Gradients for Fast ODE Solvers of Diffusion Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 1

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Observation 412f71b5-977f-48ef-8196-f906e4c77ad8 · inbound

Understanding, Accelerating, and Improving MeanFlow Training cites this paper.

Understanding, Accelerating, and Improving MeanFlow Training TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 5

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Observation d42206cd-7a12-402e-941f-144564a4f58e · inbound

B\'ezierFlow: Learning B\'ezier Stochastic Interpolant Schedulers for Few-Step Generation cites this paper.

B\'ezierFlow: Learning B\'ezier Stochastic Interpolant Schedulers for Few-Step Generation TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 1

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arxiv_id, observed 2026-05-16T21:53:35.598292Z

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

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Observation 4c7db6eb-62d3-489d-9a9d-208c9354c73f · inbound

IDLM: Inverse-distilled Diffusion Language Models cites this paper.

IDLM: Inverse-distilled Diffusion Language Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2021

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Observation be8d4604-cadf-45a1-9407-ea7cd0e9a22b · inbound

MixFlow: Mixed Source Distributions Improve Rectified Flows cites this paper.

MixFlow: Mixed Source Distributions Improve Rectified Flows TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2

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arxiv_id, observed 2026-05-11T07:30:59.911521Z

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Observation f0869ee0-2c34-4c05-92fa-49e109c19c8c · inbound

Efficient Diffusion Distillation via Embedding Loss cites this paper.

Efficient Diffusion Distillation via Embedding Loss TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 56

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arxiv_id, observed 2026-05-11T19:01:19.481544Z

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Observation 77730290-436a-49d5-85c7-c7ce40fd5531 · inbound

Midpoint Generative Models cites this paper.

Midpoint Generative Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 25

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arxiv_id, observed 2026-06-29T08:53:16.224022Z

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Observation 63385649-6104-4c7f-9fa5-6119142b0f1c · inbound

Accelerating Speculative Diffusions via Block Verification cites this paper.

Accelerating Speculative Diffusions via Block Verification TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 5

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arxiv_id, observed 2026-07-03T14:38:29.073992Z

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Observation 6e9dd898-291d-40c8-b5f2-840b48b7b781 · inbound

FDM-MFVT: Few-step Sampling Diffusion Model for Mask-Free Virtual Try-On cites this paper.

FDM-MFVT: Few-step Sampling Diffusion Model for Mask-Free Virtual Try-On TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2

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arxiv_id, observed 2026-06-30T07:44:21.521098Z

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Observation 801c03fe-804b-45b9-9904-c2a847dbade2 · inbound

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches cites this paper.

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 102

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arxiv_id, observed 2026-07-01T10:05:41.447087Z

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source=arxiv_source observed=2026-07-01T05:49:20.689248Z digest=sha256:ec0e8ff63a2ae00826f2d7f9924ea30fe17e725408aef15f1db4be5b916d3473

Observation fa36518e-7a43-42f0-818e-724cb9595fd7 · inbound

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches cites this paper.

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 102

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arxiv_id, observed 2026-07-03T22:18:59.565663Z

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source=arxiv_source observed=2026-07-03T22:14:30.734906Z digest=sha256:b747151b0837c598663d8b17e36ed9874cf81278d2ca39f4991268aed86f1ad4

Observation 403be5a9-de5f-4f3b-9ac9-42b4900706f0 · inbound

Efficient Difficulty-Aware Dynamic Routing for Diffusion-Based Real-World Image Super-Resolution cites this paper.

Efficient Difficulty-Aware Dynamic Routing for Diffusion-Based Real-World Image Super-Resolution TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 32

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Observation b45e6eb5-63d6-47e2-b7ba-fa4ec9b659e5 · inbound

Amortized Moment Matching for Visual Generation cites this paper.

Amortized Moment Matching for Visual Generation TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 73

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