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Paper Citation Record · LEDGER

Lossy Compression with Pretrained Diffusion Models

As of 15 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 3 inbound Pith citation observations for arXiv:2501.09815.

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

pith.paper-citation-record.v1
2501.09815 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:44:31.839572Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T02:50:28.619370Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:07:36.775462Z

Reference resolution

41 of 41 outbound references displayed

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  • verified fuzzy12
  • unresolved28
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a08dc145-dce8-44db-ac43-590f25dc6474 · outbound

This paper cites URL https://vcgit.hhi.fraunhofer.de/jvet/VVCSoftware_VTM.

Lossy Compression with Pretrained Diffusion Models URL https://vcgit.hhi.fraunhofer.de/jvet/VVCSoftware_VTM

Reference 1

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Source-reported events for the cited work

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Observation 899a4275-2bf0-4782-8b5e-04f35260c835 · outbound

This paper cites Muckley, Jakob Verbeek, and St \'e phane Lathuili \`e re.

Lossy Compression with Pretrained Diffusion Models Muckley, Jakob Verbeek, and St \'e phane Lathuili \`e re

Reference 2

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source=arxiv_source observed=2026-08-10T19:44:31.604412Z digest=sha256:9ba87c00c752cad766669682042547e905300c30bbbcb1e8648edb2258e95a96

Observation 95ec8c45-9bf6-4691-8946-c1ea9c084f2f · outbound

This paper cites Diffusion Posterior Sampling for General Noisy Inverse Problems.

Lossy Compression with Pretrained Diffusion Models Diffusion Posterior Sampling for General Noisy Inverse Problems

Reference 3

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Source-reported events for the cited work

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Observation 2efdb39c-b977-486f-a7b8-f6f1fb5a1521 · outbound

This paper cites PSC: Posterior Sampling-Based Compression.

Lossy Compression with Pretrained Diffusion Models PSC: Posterior Sampling-Based Compression

Reference 4

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no resolver link, observed 2026-08-10T19:44:31.620904Z

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source=arxiv_source observed=2026-08-10T19:44:31.620904Z digest=sha256:f8c43ea55abf1320aa7b434fe613c51b4721334d7d7ad963a5dddcc6c0718643

Observation c5c4bb4d-93f8-4847-9e8a-a7383bdc5d22 · outbound

This paper cites Scaling Rectified Flow Transformers for High-Resolution Image Synthesis.

Lossy Compression with Pretrained Diffusion Models Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

Reference 5

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source=arxiv_source observed=2026-08-10T19:44:31.627995Z digest=sha256:2c9887e9e19d824033f9a2f9a7c842141d7bff75087827e7bfdf8438d0fe7b9e

Observation c950c160-351c-4718-b05d-8732c3df8b07 · outbound

This paper cites Factorized Diffusion: Perceptual Illusions by Noise Decomposition.

Lossy Compression with Pretrained Diffusion Models Factorized Diffusion: Perceptual Illusions by Noise Decomposition

Reference 6

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source=arxiv_source observed=2026-08-10T19:44:31.634055Z digest=sha256:9f5ca215ead2e247172d1cd82662dd45a4999da852b29b170c06b7c669f13674

Observation e987ba1b-df7a-48f2-beca-f98c2adfd5f1 · outbound

This paper cites Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models.

Lossy Compression with Pretrained Diffusion Models Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models

Reference 7

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Observation 2f932e26-1fd2-4c49-b959-0c0dae8d4ab4 · outbound

This paper cites Elasticdiffusion: Training-free arbitrary size image generation through global-local content separation.

Lossy Compression with Pretrained Diffusion Models Elasticdiffusion: Training-free arbitrary size image generation through global-local content separation

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 25aa321f-1da4-4e73-9cfb-3e72cb491432 · outbound

This paper cites Minimal random code learning: Getting bits back from compressed model parameters.

Lossy Compression with Pretrained Diffusion Models Minimal random code learning: Getting bits back from compressed model parameters

Reference 9

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Source-reported events for the cited work

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Observation 32bfdc11-20f1-462d-904d-3feae0a59488 · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

Lossy Compression with Pretrained Diffusion Models CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 10

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Observation 2d4a90f3-e9f6-4cb4-bef5-8c729df0ba4e · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Lossy Compression with Pretrained Diffusion Models Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 11

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Observation be1373d3-8b81-4636-982a-55459a478f21 · outbound

This paper cites Denoising diffusion probabilistic models.

Lossy Compression with Pretrained Diffusion Models Denoising diffusion probabilistic models

Reference 12

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Source-reported events for the cited work

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Observation c45beb0b-260c-4dd9-9c2d-62d89c4e057d · outbound

This paper cites Generative latent coding for ultra-low bitrate image compression.

Lossy Compression with Pretrained Diffusion Models Generative latent coding for ultra-low bitrate image compression

Reference 13

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verified fuzzy
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Source-reported events for the cited work

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Observation 4a4822af-2a11-4e7f-a9f9-a6c5d71ef3bd · outbound

This paper cites Pipal: a large-scale image quality assessment dataset for perceptual image restoration.

Lossy Compression with Pretrained Diffusion Models Pipal: a large-scale image quality assessment dataset for perceptual image restoration

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 8df0f4f9-3815-4216-a7c0-3716e39f5d1b · outbound

This paper cites Variational diffusion models.

Lossy Compression with Pretrained Diffusion Models Variational diffusion models

Reference 15

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Observation a6e44dcc-a6dc-4b4c-b04a-2a978b71d452 · outbound

This paper cites Text + Sketch: Image Compression at Ultra Low Rates.

Lossy Compression with Pretrained Diffusion Models Text + Sketch: Image Compression at Ultra Low Rates

Reference 16

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Observation 0c9aec8b-a7cc-442d-bb24-7753da6d495a · outbound

This paper cites BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation.

Lossy Compression with Pretrained Diffusion Models BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Reference 17

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Observation 62cda177-64d4-4585-b9a5-660898318c71 · outbound

This paper cites Towards extreme image compression with latent feature guidance and diffusion prior.

Lossy Compression with Pretrained Diffusion Models Towards extreme image compression with latent feature guidance and diffusion prior

Reference 18

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Source-reported events for the cited work

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Observation a557ec8a-274a-440e-b0f3-d932fa2b1683 · outbound

This paper cites Flow Matching for Generative Modeling.

Lossy Compression with Pretrained Diffusion Models Flow Matching for Generative Modeling

Reference 19

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Observation c5f51f52-8de8-4660-9664-9aa89e981703 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Lossy Compression with Pretrained Diffusion Models Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 20

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Observation 5df5aa84-be11-4c9b-8a44-36d8abff2bce · outbound

This paper cites Deepcache: Accelerating diffusion models for free.

Lossy Compression with Pretrained Diffusion Models Deepcache: Accelerating diffusion models for free

Reference 21

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Observation b836aeed-3e70-48ab-9a00-e54ab575176d · outbound

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Lossy Compression with Pretrained Diffusion Models High-Fidelity Generative Image Compression

Reference 22

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Observation dc1c0ce0-d053-43c2-a12c-b98990a183e0 · outbound

This paper cites Joint autoregressive and hierarchical priors for learned image compression.

Lossy Compression with Pretrained Diffusion Models Joint autoregressive and hierarchical priors for learned image compression

Reference 23

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verified fuzzy
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Source-reported events for the cited work

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Observation aed6593f-b622-4266-b390-ca042c801242 · outbound

This paper cites Cache me if you can: Effects of dns time-to-live.

Lossy Compression with Pretrained Diffusion Models Cache me if you can: Effects of dns time-to-live

Reference 24

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Observation a0c234dd-8b07-4bfc-b59e-d2601f7568e0 · outbound

This paper cites Improving statistical fidelity for neural image compression with implicit local likelihood models.

Lossy Compression with Pretrained Diffusion Models Improving statistical fidelity for neural image compression with implicit local likelihood models

Reference 25

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Source-reported events for the cited work

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Observation 0f7ddc3e-6b6c-4768-aab7-39fa91d730e8 · outbound

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

Lossy Compression with Pretrained Diffusion Models SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 26

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Observation c5ea973a-c818-4b42-b428-fe5012250191 · outbound

This paper cites Barron, and Ben Mildenhall.

Lossy Compression with Pretrained Diffusion Models Barron, and Ben Mildenhall

Reference 27

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Observation 7ed8cd6c-c56e-48e1-9698-d4692e213f08 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Lossy Compression with Pretrained Diffusion Models Deep unsupervised learning using nonequilibrium thermodynamics

Reference 28

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Observation c753b036-e60d-4c71-ab97-21f03c34157f · outbound

This paper cites Denoising Diffusion Implicit Models.

Lossy Compression with Pretrained Diffusion Models Denoising Diffusion Implicit Models

Reference 29

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Observation c9d9de42-e4be-4ecc-9501-cb1e3a6b2a2f · outbound

This paper cites Lossy Compression with Gaussian Diffusion.

Lossy Compression with Pretrained Diffusion Models Lossy Compression with Gaussian Diffusion

Reference 30

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Observation b6fe8674-bcea-4042-9494-e35baa4b1d21 · outbound

This paper cites Algorithms for the communication of samples.

Lossy Compression with Pretrained Diffusion Models Algorithms for the communication of samples

Reference 31

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b7a63074-b11d-4234-b11d-83b93b57c40e · outbound

This paper cites Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery.

Lossy Compression with Pretrained Diffusion Models Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery

Reference 32

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Observation 18c247dc-6d88-44e6-808f-65e647ef53c9 · outbound

This paper cites Stable diffusion --- Wikipedia , the free encyclopedia, 2024.

Lossy Compression with Pretrained Diffusion Models Stable diffusion --- Wikipedia , the free encyclopedia, 2024

Reference 33

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verified fuzzy
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Source-reported events for the cited work

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Observation 45fd7e41-2f02-4260-a3a3-0255e23a81ad · outbound

This paper cites Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels.

Lossy Compression with Pretrained Diffusion Models Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels

Reference 34

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source=arxiv_source observed=2026-08-10T19:44:31.801010Z digest=sha256:a10fb49c62139bb4e33175873344b85e155494fa43ad9e4e76bb9c4ca7b44298

Observation c4144186-1b5a-4035-bac7-da8ff8d77d66 · outbound

This paper cites Lossy image compression with conditional diffusion models.

Lossy Compression with Pretrained Diffusion Models Lossy image compression with conditional diffusion models

Reference 35

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7cc0e76c-7ebf-4b21-bae2-f955aece019c · outbound

This paper cites Adding conditional control to text-to-image diffusion models, 2023.

Lossy Compression with Pretrained Diffusion Models Adding conditional control to text-to-image diffusion models, 2023

Reference 36

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Observation 19da7b80-54c9-482e-8c52-930c32c2ed4b · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Lossy Compression with Pretrained Diffusion Models The unreasonable effectiveness of deep features as a perceptual metric

Reference 37

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Lossy Compression with Pretrained Diffusion Models write newline

Reference 38

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This paper cites @esa (Ref.

Lossy Compression with Pretrained Diffusion Models @esa (Ref

Reference 39

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Lossy Compression with Pretrained Diffusion Models Unresolved cited work

Reference 40

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Lossy Compression with Pretrained Diffusion Models Unresolved cited work

Reference 41

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Pith citing papers

Observation 7f85470a-b56b-4474-a118-dd812fab6b9c · inbound

GVCC: Zero-Shot Video Compression via Codebook-Driven Stochastic Rectified Flow cites this paper.

GVCC: Zero-Shot Video Compression via Codebook-Driven Stochastic Rectified Flow Lossy Compression with Pretrained Diffusion Models

Reference 33

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Observation 21381e10-1465-447c-a034-7ee091d7ea96 · inbound

Few-step Generative Models as Lossy Compression cites this paper.

Few-step Generative Models as Lossy Compression Lossy Compression with Pretrained Diffusion Models

Reference 17

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Observation f21b0cc9-f41e-4b4f-b1cd-2590117892c1 · inbound

Scalable Differentially Private Data Compression via Diffusion and Stochastic Codes cites this paper.

Scalable Differentially Private Data Compression via Diffusion and Stochastic Codes Lossy Compression with Pretrained Diffusion Models

Reference 10

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