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Paper Citation Record · LEDGER

Generating Images with Sparse Representations

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 41 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 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 41 of 41 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T23:46:22.525797Z

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T11:16:28.445702Z digest=sha256:a587513524d7fd8d5349b7e4851261900ddd2243cc38d722092fad181681de24

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-16T18:40:37.277580Z digest=sha256:b9be96519ad62ad74fabcb17bb701244bf5799ca77069bc4303c481593ac65b1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T06:04:05.434354Z digest=sha256:79b3d89d8a2548b4fe51d73592518495f910f70e278a852ae475c30d9e615996

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T22:09:16.622717Z digest=sha256:febf3cb64d9ee13567ff1aa1938c50f0f0f2228d9d453e6138e05b4dbe40a58c

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:46:22.525797Z digest=sha256:4fd83f72efc819c898967047693e80f6806e1b9b3087b225d388d736fe70a9c2

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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no resolver link, observed 2026-08-08T15:17:12.739960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:17:12.739960Z digest=sha256:f6ea6de6bafb0b08cd134759c514ab35f1364e3921b678c78e125bf521c5f42d

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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no resolver link, observed 2026-08-07T21:17:55.958323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.958323Z digest=sha256:643fbc2602367fc0b8f7087d131dfdf0f20c6ada81d0eeef21dd7f7454d76dcd

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=sha256:5f5d267e619583dba94a9c87cbb9285f77a4c06cdbc2d40010000ea46ea21420

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=sha256:8bb4c9da0ec07b06e5a71ebf346f50397215ff4faf6370c6fac6c48053ff24c9

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:c5807f0e4aef9ca1ef6fd2750fff3033014ef0af743ce95c53365129b566ec9d

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=sha256:09ad3ae879cd0aa09bd826570544723fafc504e00a53765138cf403b55add4f3

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=sha256:45ff52b772726033226d5aad60a1d3d4b2b970d0473ae00416675390ac6a682e

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:54.418614Z digest=sha256:e9c054c80d2ff146eeb0fa6de3578eea7e12e734bf7b4c04eacf34952dfd2c66

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-22T13:11:39.719989Z digest=sha256:efff057e3389bea3ea390afd2c5f0d41a96536360effcc1fc8f3be37f3529931

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T05:22:05.125849Z digest=sha256:5cb98405b321349ed0526c2e32b2f74f82043b23c046081b0506aac1031fbb0a

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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verified exact
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T05:47:24.669763Z digest=sha256:1c7eaf86148c78f4830a5304a0b7b3b2b4dca48e1febf808604dd0263a5e6683

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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no resolver link, observed 2026-08-03T15:34:57.891744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:34:57.891744Z digest=sha256:65498f03305d1bc7a9c89c4d82fa2265b2a06365bb22de5f409743a58125861c

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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unresolved
no resolver link, observed 2026-08-03T11:04:32.426917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:04:32.426917Z digest=sha256:d8a91ca4d185b6054aa37751dfb1d3571c48fc2a81796ca1cf9fefe8f3a4919a

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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verified exact
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T12:16:16.461488Z digest=sha256:34e0ea058ca3c3b679f766b566db2842551bed9a4ff9868bd2a7aff0ac85f39b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T18:41:38.616611Z digest=sha256:0954f92a8a7c3bb79a2bf9265f2395b3c30508f0e179d99ad2465ed5a99a0855

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T18:55:26.852585Z digest=sha256:4c6b0212aa5b005d5548494f243bbfd6ab7080e6376f79be062ef5cedbd93708

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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metadata mismatch
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T06:30:52.371482Z digest=sha256:b3361c2350bb722d7364d3355e563135e57522de294d62c9a7d564929a0454b0

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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verified exact
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T17:16:00.988125Z digest=sha256:0302efab82892e8a30bf0700f806c142e218031b6281b7ade61f47566032f811

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T04:08:11.110912Z digest=sha256:dd4d8c8662531d9e4f6fcf6d39c5d81989a2c5f8a4116791a07f83b0d92ec0af

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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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T21:50:57.770557Z digest=sha256:ab0da33c197aa83d3f568ffc21946aa585f11de3dd506496d42356e695c48c21

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T19:08:26.689023Z digest=sha256:942aeb40eb684aceb0cbbb78105a866bd59fbaddcab0ffa42332f2e4aaddec0e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T19:33:53.876614Z digest=sha256:e90c18f8e5e06b023d18bb06e02078c0f7146e137637c7ff86c240202be18bec

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-20T22:41:44.510546Z digest=sha256:00f4da87f7a8bed00d55ebd833889408cfd282f20f1606d4caf6a780c5ca91b6

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-19T20:49:25.902880Z digest=sha256:09c02b571249d9a6bbe4f666a0a2a879643c93472c66583b3b95fb544d8c7d56

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T15:09:47.753331Z digest=sha256:36ff0b2487d5460610021c6df65e8a2d62c877bacc18ebb63f929666080b5410

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T12:05:00.204261Z digest=sha256:fafa1a979821a3b23b2201d971b53dc850dc54b59fb6734af903dbad45bb6e98

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

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T07:47:44.501736Z digest=sha256:4f90827c96f15e4168c59f5f74f4f4b4744bbd8f44bb204ba4faab8e189f5496

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T19:23:08.100056Z digest=sha256:2ef4acd57d1f549814a090b916be0fa4080100613ba0dc9aa569ee57602ac691

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T18:44:41.266768Z digest=sha256:27e47436357ae861ffcec512935601e16312889c3afe7c93605c061becd468ac

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-07-01T05:49:20.689248Z digest=sha256:a0bd986704042ca4bd297283238df063e0598cb6a9890cd5f7d8f8bb0c9a1b3c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-07-03T22:14:30.734906Z digest=sha256:da7dfb70579f101e409847b302206d02592ff9ea154dfa432567781e2f2e8d67

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-07-02T13:54:02.092771Z digest=sha256:39172ef6cfd1fa832952e6341b86346b9b2b8a465e0f805ca056a0306d0584b4

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:e491d7264dd18cdf01f5ea4ef9cc66d33bc86b206db3180796939ebef25c9425

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-03T14:36:59.833888Z digest=sha256:8435bb03ea0a1218b8ee45e9cc127a555a36917492be6c4d45d4b92211411303

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=sha256:6aa8ed508af3367d6965d05e903583febc51f33509623dcbdc1820dd892cbb13

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:e464336d27e0efa4df2ddd501114d81d792a6111f0d2749355fd12a5c4326d77