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Paper Citation Record · LEDGER

Generating Images with Sparse Representations

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 50 inbound Pith citation observations for arXiv:2103.03841.

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

pith.paper-citation-record.v1
2103.03841 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 50 of 50 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:27:31.682983Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T22:18:59.593848Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3bb42088-30ba-41fb-99c2-1b549de76332 · inbound

Diffusion Models Beat GANs on Image Synthesis cites this paper.

Diffusion Models Beat GANs on Image Synthesis Generating Images with Sparse Representations

Reference 42

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arxiv_id, observed 2026-05-13T11:16:28.599550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T11:16:28.445702Z digest=sha256:e47df7161230f09b2c968dddb29d3d1ede2445c726888bb64da8904657426f87

Observation eb60cf62-7000-4c85-9cf7-c3cc071cab1d · inbound

Vector-quantized Image Modeling with Improved VQGAN cites this paper.

Vector-quantized Image Modeling with Improved VQGAN Generating Images with Sparse Representations

Reference 48

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arxiv_id, observed 2026-05-16T18:40:37.425326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-16T18:40:37.277580Z digest=sha256:bc63a3db1bac479d04d61102681cb148dafc00919fca1e8a9e24e8106d170820

Observation fafa125d-ba17-42cd-abf7-e15109c99547 · inbound

Scalable Diffusion Models with Transformers cites this paper.

Scalable Diffusion Models with Transformers Generating Images with Sparse Representations

Reference 34

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arxiv_id, observed 2026-05-12T06:04:05.587497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T06:04:05.434354Z digest=sha256:3ec849cad62ed8d2efec5cd4c69da428cb608af80aa1b077627be4b0892c000e

Observation d09ff31e-3157-4174-9739-2cb6482f1207 · inbound

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation cites this paper.

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation Generating Images with Sparse Representations

Reference 21

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arxiv_id, observed 2026-05-11T22:09:16.973774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-11T22:09:16.622717Z digest=sha256:1b104033f5b5e62e60191c46261ca2d9f801ea8978cb47543bb718db9630b03b

Observation cea0d3fe-b486-4c11-b0fe-0f5846e1de55 · inbound

MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models cites this paper.

MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models Generating Images with Sparse Representations

Reference 32

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no resolver link, observed 2026-08-11T14:55:03.459710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:55:03.459710Z digest=sha256:d1e25e15837c60be901e45561ee45b80c45a5b051410f36ba6f0dffb349582a6

Observation 60d99a5c-62c6-4bfa-838d-ac51c569babf · inbound

Numerical Pruning for Efficient Autoregressive Models cites this paper.

Numerical Pruning for Efficient Autoregressive Models Generating Images with Sparse Representations

Reference 111

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-11T14:11:27.207683Z digest=sha256:96f1a1ed29b61cd6f377760a0e502d1a21590871473fcdda44d64cb250bf6cc9

Observation 1393505b-7e83-459f-ab6f-ced414968cda · inbound

LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers cites this paper.

LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers Generating Images with Sparse Representations

Reference 102

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no resolver link, observed 2026-08-11T14:11:39.794200Z

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source=arxiv_source observed=2026-08-11T14:11:39.794200Z digest=sha256:beacdc480669ad18bd488ee54ec757b975f9b1ccca689eec9a6e04617a701e26

Observation 736f728d-acef-4d38-b110-d6fd854235a1 · inbound

Parallel Sequence Modeling via Generalized Spatial Propagation Network cites this paper.

Parallel Sequence Modeling via Generalized Spatial Propagation Network Generating Images with Sparse Representations

Reference 70

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:16:43.706301Z digest=sha256:d4c833970bb886cf706f69dc37d3f2776834bbfccaaea0a56365a217881a4580

Observation ce385fa0-cd6e-4835-8bca-2517633193c4 · inbound

TQ-DiT: Efficient Time-Aware Quantization for Diffusion Transformers cites this paper.

TQ-DiT: Efficient Time-Aware Quantization for Diffusion Transformers Generating Images with Sparse Representations

Reference 30

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no resolver link, observed 2026-08-08T23:46:22.525797Z

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source=pdf_text observed=2026-08-08T23:46:22.525797Z digest=sha256:29d47208b1dba1e23cf3b88ff0ef91b2c118c641b87e51b44377db4e15b3e16e

Observation 9a2435dd-d232-4aad-a51e-713826ef14a2 · inbound

Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation cites this paper.

Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation Generating Images with Sparse Representations

Reference 2020

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:17:12.739960Z digest=sha256:2599569044d0756b7c6c2b7bc2ab6191f048960f201a92d5c2ae51c89289b5ab

Observation 2b34da8c-626a-442d-b5c6-c4c3a1f8c517 · inbound

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling cites this paper.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Generating Images with Sparse Representations

Reference 2017

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.958323Z digest=sha256:bbe0c737cae9cd681d8f971c850353890a98e2680d9671cc218e0e4030400694

Observation fed25d66-1905-4700-a151-2d1baa508acc · inbound

Adept: Annotation-Denoising Auxiliary Tasks with Discrete Cosine Transform Map and Keypoint for Human-Centric Pretraining cites this paper.

Adept: Annotation-Denoising Auxiliary Tasks with Discrete Cosine Transform Map and Keypoint for Human-Centric Pretraining Generating Images with Sparse Representations

Reference 30

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no resolver link, observed 2026-08-16T05:27:31.682983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:27:31.682983Z digest=sha256:483fed1219c63112b099cf4e064437c14df2ce88365a1ff9f44e4b0581f9c0f9

Observation 20ac4711-1ac7-4e0e-90bf-376c4fe47943 · inbound

Text to Image Generation and Editing: A Survey cites this paper.

Text to Image Generation and Editing: A Survey Generating Images with Sparse Representations

Reference 177

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no resolver link, observed 2026-08-16T00:53:12.405051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:53:12.405051Z digest=sha256:3960a41c295984ba1bd6a15c3ef1277e458313f3bda32d358bc387152673f03b

Observation 4778b57f-3298-40fb-a010-96aab305062c · inbound

Image Classification Using a Diffusion Model as a Pre-Training Model cites this paper.

Image Classification Using a Diffusion Model as a Pre-Training Model Generating Images with Sparse Representations

Reference 24

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no resolver link, observed 2026-08-15T22:35:15.514423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:35:15.514423Z digest=sha256:d8433064f864804900db34548c1b7c50cd4fe91175be2ab41dd91c6a442d2dc7

Observation 176abfe9-1a39-4f1a-9b10-41cea373b490 · inbound

Native-Resolution Image Synthesis cites this paper.

Native-Resolution Image Synthesis Generating Images with Sparse Representations

Reference 50

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no resolver link, observed 2026-08-07T11:15:25.847259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:15:25.847259Z digest=sha256:c7a55a5f3237ea9b0bf95530fb7ce09093a904571a47d1241c68411c34dbf335

Observation 1a8088d6-0f35-41f8-8cd6-9de4844306bf · inbound

Contrastive Flow Matching cites this paper.

Contrastive Flow Matching Generating Images with Sparse Representations

Reference 30

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no resolver link, observed 2026-08-07T10:31:22.919748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:31:22.919748Z digest=sha256:de0de5574fc83470ccdbd33c60255d0d9eb9a20b32d0ec630ca27cc9dde54bea

Observation 0e01c73a-7991-4632-beb1-d78244652435 · inbound

MPQ-DMv2: Flexible Residual Mixed Precision Quantization for Low-Bit Diffusion Models with Temporal Distillation cites this paper.

MPQ-DMv2: Flexible Residual Mixed Precision Quantization for Low-Bit Diffusion Models with Temporal Distillation Generating Images with Sparse Representations

Reference 68

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no resolver link, observed 2026-08-06T19:57:23.528462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:57:23.528462Z digest=sha256:9217f539cb4b2c10041674906b984fce0ad1d2ea93e61754e7808799e3338dd9

Observation 5b23831b-79bb-415c-8e7d-09c391e8325a · inbound

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization cites this paper.

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization Generating Images with Sparse Representations

Reference 44

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no resolver link, observed 2026-08-06T16:42:12.103819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:42:12.103819Z digest=sha256:9f5ba57e366931bef794ca83113c5380e77698d2b086a3858233071394fdd7f2

Observation fb840580-43b4-4d38-8a66-d564d86f3fd4 · inbound

PixNerd: Pixel Neural Field Diffusion cites this paper.

PixNerd: Pixel Neural Field Diffusion Generating Images with Sparse Representations

Reference 48

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no resolver link, observed 2026-08-06T10:59:53.805944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:59:53.805944Z digest=sha256:4a99cd83de4e07f09fb28d0f9be023e76de108844b61c3e3bffa1247b2d36d24

Observation f35942ee-5150-4fb7-8a59-f103fc565df6 · inbound

Transition Models: Rethinking the Generative Learning Objective cites this paper.

Transition Models: Rethinking the Generative Learning Objective Generating Images with Sparse Representations

Reference 50

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no resolver link, observed 2026-08-05T10:19:54.418614Z

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source=pdf_text observed=2026-08-05T10:19:54.418614Z digest=sha256:9e9e48d9a8157cdfb60d0a0c2ebfa9b153c712014fb48851e0983a56d4f6a645

Observation 960ea0de-5563-4e97-9f30-074304f1fec1 · inbound

InfGen: A Resolution-Agnostic Paradigm for Scalable Image Synthesis cites this paper.

InfGen: A Resolution-Agnostic Paradigm for Scalable Image Synthesis Generating Images with Sparse Representations

Reference 21

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no resolver link, observed 2026-08-15T15:58:17.620313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:58:17.620313Z digest=sha256:9baf338052a5928516d4830349c02e3dda1504808a0e1d49801679cbb239ca55

Observation 00ecacd5-65d9-4567-b4c2-62113295409f · inbound

RobuQ: Pushing DiTs to W1.58A2 via Robust Activation Quantization cites this paper.

RobuQ: Pushing DiTs to W1.58A2 via Robust Activation Quantization Generating Images with Sparse Representations

Reference 48

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verified exact
arxiv_id, observed 2026-05-22T13:14:53.442419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-22T13:11:39.719989Z digest=sha256:84c066710cc548d02e9d50546d53e4cc902771a4886136e6dad10ce57cf181a4

Observation 5d12265c-8fa6-4846-afe2-2fffda004a88 · inbound

VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models cites this paper.

VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models Generating Images with Sparse Representations

Reference 14

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arxiv_id, observed 2026-05-18T05:22:23.936822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-18T05:22:05.125849Z digest=sha256:74d14cdba9e9873760bd292130fa79b7fa55f9b74b478595123f28412a22d3f6

Observation 6de1cbcf-b57c-4520-aa1e-6bdb578f8f9f · inbound

DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation cites this paper.

DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation Generating Images with Sparse Representations

Reference 40

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arxiv_id, observed 2026-05-17T05:49:08.289573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-17T05:47:24.669763Z digest=sha256:6d13d236e969b519bddd1c3681272cf9bf7852303a09b8313f84628318c41361

Observation 331bbeef-cae5-40a4-ae90-53715113fa99 · inbound

REGLUE Your Latents with Global and Local Semantics for Entangled Diffusion cites this paper.

REGLUE Your Latents with Global and Local Semantics for Entangled Diffusion Generating Images with Sparse Representations

Reference 46

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:34:57.891744Z digest=sha256:8f6cb565ff09a7af0f0b4c2471732d8ced3a0a0a484ca0a078b9653bf1960541

Observation 6f9f2409-fc7d-49a6-869d-4cc32f5d620a · inbound

Self-transcendence: Is External Feature Guidance Indispensable for Accelerating Diffusion Transformer Training? cites this paper.

Self-transcendence: Is External Feature Guidance Indispensable for Accelerating Diffusion Transformer Training? Generating Images with Sparse Representations

Reference 29

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:04:32.426917Z digest=sha256:3d185d01d66f15dc0a3fb9742dae17f2be8d112099f472bdfb24567cf44812dc

Observation 8a57058c-3c67-47c2-b5ec-fe5f6ed14860 · inbound

Mirai: Autoregressive Visual Generation Needs Foresight cites this paper.

Mirai: Autoregressive Visual Generation Needs Foresight Generating Images with Sparse Representations

Reference 27

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arxiv_id, observed 2026-05-16T12:17:52.093185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-16T12:16:16.461488Z digest=sha256:003a188eba342bc25c4fddf533d452b34edec51119548118cf39c4eb2b84a2d9

Observation 49fdeb4c-0e2f-4f21-92cf-fd07baffdeea · inbound

Evolution of Video Generative Foundations cites this paper.

Evolution of Video Generative Foundations Generating Images with Sparse Representations

Reference 127

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arxiv_id, observed 2026-05-11T00:05:51.579684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T18:41:38.616611Z digest=sha256:5f24727d9c5e00150152622321b7d9e5d5d0a05a35631e29b23cffe8eecf3175

Observation ef7356c1-fcd7-4285-b368-3c282918aa69 · inbound

Data Warmup: Complexity-Aware Curricula for Efficient Diffusion Training cites this paper.

Data Warmup: Complexity-Aware Curricula for Efficient Diffusion Training Generating Images with Sparse Representations

Reference 23

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arxiv_id, observed 2026-05-10T23:40:54.089923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T18:55:26.852585Z digest=sha256:697442909fcbaef295df163e099ea9aff79cac1d2f9a00301d48645e093f7a73

Observation 1afb4c50-ad26-4ec0-b096-05bed2769647 · inbound

Coevolving Representations in Joint Image-Feature Diffusion cites this paper.

Coevolving Representations in Joint Image-Feature Diffusion Generating Images with Sparse Representations

Reference 30

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arxiv_id, observed 2026-05-10T06:31:30.434265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T06:30:52.371482Z digest=sha256:23b7768f18c3a25ff32000260a28ef6eabbfb1513dd52de718f617b688898d02

Observation 6541298c-df1f-44b1-96b8-4aba0280e16a · inbound

The Thinking Pixel: Recursive Sparse Reasoning in Multimodal Diffusion Latents cites this paper.

The Thinking Pixel: Recursive Sparse Reasoning in Multimodal Diffusion Latents Generating Images with Sparse Representations

Reference 39

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arxiv_id, observed 2026-05-11T23:21:24.694399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-07T17:16:00.988125Z digest=sha256:a75ec45cf1c5d1897e66f6e5ac4f7b0c877149f8c40953b2c280aae82c0bef5f

Observation daf51376-675f-4420-a9ff-06f6317c6e69 · inbound

Elucidating Representation Degradation Problem in Diffusion Model Training cites this paper.

Elucidating Representation Degradation Problem in Diffusion Model Training Generating Images with Sparse Representations

Reference 41

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arxiv_id, observed 2026-05-12T06:36:26.452150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T04:08:11.110912Z digest=sha256:d2d4e3b5252112886e6d15e38b832259508c3e45fbbd90c8011d1cacbda0e22a

Observation dd0ab9b1-aa81-4985-8126-cfba8be58c7e · inbound

The Velocity Deficit: Initial Energy Injection for Flow Matching cites this paper.

The Velocity Deficit: Initial Energy Injection for Flow Matching Generating Images with Sparse Representations

Reference 2

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verified exact
arxiv_id, observed 2026-06-30T21:55:05.899541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T21:50:57.770557Z digest=sha256:baefca511a8638dc2c180dc7c9fa923aa0012c655283a97aeae214defca80ff1

Observation 58cd0f0d-8f91-4bb3-bbae-890d5abd8776 · inbound

HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion cites this paper.

HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion Generating Images with Sparse Representations

Reference 44

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arxiv_id, observed 2026-05-20T19:08:53.996058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-20T19:08:26.689023Z digest=sha256:7cf8c85001f4b0bf1be0a1fd3205607ad1e7a96d171eeca31ca9ccb39b5fc375

Observation 367d6c1d-5065-4887-904f-0a2a03bd19e1 · inbound

HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion cites this paper.

HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion Generating Images with Sparse Representations

Reference 44

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arxiv_id, observed 2026-06-30T19:35:00.964064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T19:33:53.876614Z digest=sha256:767f4136b9dc39aac3842c5f45f983c8afd825ddb8704eaaad68e111f3455cff

Observation dd6592cb-2633-4c4e-a7b0-c81c8973e149 · inbound

Mutual Enhancement Between Global Tokens and Patch Tokens: From Theory to Practice cites this paper.

Mutual Enhancement Between Global Tokens and Patch Tokens: From Theory to Practice Generating Images with Sparse Representations

Reference 34

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metadata mismatch
arxiv_id, observed 2026-05-20T22:43:51.050270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-20T22:41:44.510546Z digest=sha256:68bae756f997e196f1c7ead64ae0c222147f4aed448605891288b8e2f3c5aa50

Observation 47625283-bc04-4477-89f2-219455b6f51c · inbound

Beyond Point-Wise Matching: Structural Representation Alignment for Accelerating Diffusion Transformers cites this paper.

Beyond Point-Wise Matching: Structural Representation Alignment for Accelerating Diffusion Transformers Generating Images with Sparse Representations

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:52:46.150164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T20:49:25.902880Z digest=sha256:fa8eb7bf5ecb86539d8c319cbd9e6992b94174fa7129883b74446436b5f605d0

Observation 2acaee13-0571-4f0d-8713-680b2dfbfba0 · inbound

Beyond Generative Priors: Minority Sampling with JEPA-Guided Diffusion cites this paper.

Beyond Generative Priors: Minority Sampling with JEPA-Guided Diffusion Generating Images with Sparse Representations

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T15:14:46.977147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T15:09:47.753331Z digest=sha256:c0173e4e3a5c3e164b43df0577763e8e5e530fa56699b394fd9bf8739b15e1a3

Observation 7b106a76-05fe-4e62-93d4-054cbc544635 · inbound

Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal cites this paper.

Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal Generating Images with Sparse Representations

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-06-29T12:13:27.005495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-29T12:05:00.204261Z digest=sha256:f72e44fac6e2bd9d2a1c7f9e1a19fb31009c10733925f93036f4d4afa69ca612

Observation b5a60490-6d24-462b-83a6-3838099ac76e · inbound

Colored Noise Diffusion Sampling cites this paper.

Colored Noise Diffusion Sampling Generating Images with Sparse Representations

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-06-29T07:53:13.707150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-29T07:47:44.501736Z digest=sha256:4e731401c181cb6dfcc100ed3a1a548ee6bb92562f650e5e8b91ca6a3f757dd9

Observation 89947199-e67e-4188-8e02-628b3c471891 · inbound

Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders cites this paper.

Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders Generating Images with Sparse Representations

Reference 86

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T19:32:35.215164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-28T19:23:08.100056Z digest=sha256:7003fb4da3338d4b739c0ce14ab41cddfb327bff078a19b5c7358b8b27291a53

Observation 410aae14-7a70-4157-8f0b-7fdfca4a93ef · inbound

MaskAlign: Token-Subset Representation Alignment for Efficient Diffusion Training cites this paper.

MaskAlign: Token-Subset Representation Alignment for Efficient Diffusion Training Generating Images with Sparse Representations

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:37:26.206062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-27T18:44:41.266768Z digest=sha256:960fc25ad1b22668b02526853821fa73a24c324d613cb0b55dc30126d986d897

Observation 88459195-5f72-4a9f-bb5a-82f36b297981 · inbound

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

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches Generating Images with Sparse Representations

Reference 86

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T10:05:41.482025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-07-01T05:49:20.689248Z digest=sha256:1fae2b0b853c44cac00606da641f2498093eaae5d2307dac4b78f30adeb5cca2

Observation f3f0c900-8548-43b5-a7b3-edaee62dc6e8 · inbound

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

Language-Assisted Super-Resolution from Real-World Low-Resolution Patches Generating Images with Sparse Representations

Reference 86

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T22:18:59.595244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-07-03T22:14:30.734906Z digest=sha256:452fc6ad7c792f58886a9c53074776003741c9d353e0e896279bf40a4d59e89a

Observation 0f66e478-2329-4d4c-b378-4b3ec6357b67 · inbound

Post-Training Pruning for Diffusion Transformers cites this paper.

Post-Training Pruning for Diffusion Transformers Generating Images with Sparse Representations

Reference 34

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T13:56:59.086466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-07-02T13:54:02.092771Z digest=sha256:69dd4300dd664d115e9f8662bdb52289f003411bb983756662ea0adc900b4a45

Observation 8e1b9f8d-9a0c-48b8-91f2-3b5a5c2038c9 · inbound

Post-Training Pruning for Diffusion Transformers cites this paper.

Post-Training Pruning for Diffusion Transformers Generating Images with Sparse Representations

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-12T09:09:54.360897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T09:09:54.360897Z digest=sha256:22bb850114c3b5dace300982ae785a3900da593e3ecf658f12954e67aefe157d

Observation 01030ea7-f018-41b9-a874-ba74ffa6394d · inbound

Post-Training Pruning for Diffusion Transformers cites this paper.

Post-Training Pruning for Diffusion Transformers Generating Images with Sparse Representations

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-15T15:42:27.162979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:42:27.162979Z digest=sha256:5d5d00775f91e53d9be078fd7a0f35f823d395b7513708c9381dfc4c165e19c8

Observation 0cd8ab5d-ec3e-42ba-98f9-c85d49e10bba · inbound

From SRA to Self-Flow: Data Augmentation or Self-Supervision? cites this paper.

From SRA to Self-Flow: Data Augmentation or Self-Supervision? Generating Images with Sparse Representations

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:38:28.525994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-03T14:36:59.833888Z digest=sha256:d4177e89687a7661943ff3126f734a8c4b587ea2ee3b6c77852353b8e31203f7

Observation 3be140c4-44e9-4122-bf43-676c28b8ea3c · inbound

MentalThink: Shaping Thoughts in Mental SVG World cites this paper.

MentalThink: Shaping Thoughts in Mental SVG World Generating Images with Sparse Representations

Reference 55

Resolution
unresolved
no resolver link, observed 2026-07-12T01:50:59.184754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T01:50:59.184754Z digest=sha256:da94268ececec7e0e1925bab3790e03044374d6d9e8a930eb0086e83cb43ff6d

Observation 194229d0-df29-40c5-9d3e-f7f97d4b754c · inbound

SPARE: Structural Parameter-Free Affinity Regularization for Flow Matching cites this paper.

SPARE: Structural Parameter-Free Affinity Regularization for Flow Matching Generating Images with Sparse Representations

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-04T17:12:36.693893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T17:12:36.693893Z digest=sha256:5ce85528d1939bbba75d6219f300bc676625f6ee38f2448c4f572edef62bbc42