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Paper Citation Record · LEDGER

Fast Training of Diffusion Models with Masked Transformers

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 39 inbound Pith citation observations for arXiv:2306.09305.

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

pith.paper-citation-record.v1
2306.09305 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 39 of 39 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 39 of 39 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:31:29.051222Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:59:57.977754Z

Reference resolution

0 of 0 outbound references displayed

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 259772ae-d76a-4d13-8ab0-b3a869a452e7 · inbound

Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation cites this paper.

Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation Fast Training of Diffusion Models with Masked Transformers

Reference 241

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arxiv_id, observed 2026-05-13T20:06:44.709299Z

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

source=arxiv_source observed=2026-05-13T20:06:44.480769Z digest=sha256:8fd2f67d0378b60927b019da812a6f4ab23b7ede176105219ffcb64b0c5b9f4e

Observation 62ff35ec-0675-42b6-b596-5828acd7c3c0 · inbound

LaVin-DiT: Large Vision Diffusion Transformer cites this paper.

LaVin-DiT: Large Vision Diffusion Transformer Fast Training of Diffusion Models with Masked Transformers

Reference 81

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:31:29.051222Z digest=sha256:ea665ce5512e4d616670022c0fc1a24790e26a328e9fa54fda1cc6f105a98068

Observation e911b030-c58c-4527-98b0-1ae3ce5ef19b · inbound

INRFlow: Flow Matching for INRs in Ambient Space cites this paper.

INRFlow: Flow Matching for INRs in Ambient Space Fast Training of Diffusion Models with Masked Transformers

Reference 73

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no resolver link, observed 2026-08-11T22:12:27.514147Z

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source=arxiv_source observed=2026-08-11T22:12:27.514147Z digest=sha256:6ff666e8a9686dea343e7bb41227e2cf6adae345b3a61781ad4ff404ae542cd5

Observation 18ab7e93-b2b8-4d33-b6d6-936aa6fae1bc · inbound

Remix-DiT: Mixing Diffusion Transformers for Multi-Expert Denoising cites this paper.

Remix-DiT: Mixing Diffusion Transformers for Multi-Expert Denoising Fast Training of Diffusion Models with Masked Transformers

Reference 40

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no resolver link, observed 2026-08-11T20:37:01.962804Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:37:01.962804Z digest=sha256:61940027b0943b1446de4811b5ec609d4860c1f6e83c5b17046756b754cf30a6

Observation 3343cfab-9a23-4c18-93b7-b4968e06e0f8 · inbound

Causal Diffusion Transformers for Generative Modeling cites this paper.

Causal Diffusion Transformers for Generative Modeling Fast Training of Diffusion Models with Masked Transformers

Reference 73

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no resolver link, observed 2026-08-11T14:20:49.571961Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:20:49.571961Z digest=sha256:e7af26f78b24fc630c9b2ee48a1886e1a31f474916f4d2e7d957809f04a2c235

Observation 79d7d66e-c587-4e38-8cd1-03f8cdf3894c · inbound

Improving Generative Pre-Training: An In-depth Study of Masked Image Modeling and Denoising Models cites this paper.

Improving Generative Pre-Training: An In-depth Study of Masked Image Modeling and Denoising Models Fast Training of Diffusion Models with Masked Transformers

Reference 42

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no resolver link, observed 2026-08-11T01:02:56.117688Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T01:02:56.117688Z digest=sha256:a900f7c1dc558fcf2393ea5dc2d7e2f9e715ed2de7c094d869812f19c0fa8eec

Observation 2f5d5819-a497-423e-bfa0-39fc45d5d85f · inbound

Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models cites this paper.

Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models Fast Training of Diffusion Models with Masked Transformers

Reference 47

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no resolver link, observed 2026-08-10T22:34:14.559949Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:34:14.559949Z digest=sha256:5e1d4ffa21cc7fe426fc62d94fe6edf3a08c0cc481325b956e5451beb8cacf00

Observation eea0c7b9-9832-46ec-9bed-6bf4cc9eda5d · inbound

Exploring Representation-Aligned Latent Space for Better Generation cites this paper.

Exploring Representation-Aligned Latent Space for Better Generation Fast Training of Diffusion Models with Masked Transformers

Reference 24

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no resolver link, observed 2026-08-09T19:22:41.755072Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:22:41.755072Z digest=sha256:3b75d652f5e2a70e258def216941c4c203dc8a255cf04df045c18f824840e2c7

Observation 8ad5099c-9541-4c90-933b-d69adb866c68 · inbound

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

Masked Generative Nested Transformers with Decode Time Scaling Fast Training of Diffusion Models with Masked Transformers

Reference 45

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no resolver link, observed 2026-08-09T19:21:56.339709Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T19:21:56.339709Z digest=sha256:d552f86280857a1a8c58007bcfcc7f67241d47b6c014f5caf510c1659370ac19

Observation 001834eb-dab0-447b-82ee-3f5c530f4a75 · 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 Fast Training of Diffusion Models with Masked Transformers

Reference 17

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no resolver link, observed 2026-08-07T21:17:55.982594Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.982594Z digest=sha256:d4dd8286b0114efd9e9b5bee270adc1029cd72a2f2265b2bec20f19e1d7e0dbd

Observation 7edd54e0-07dd-485b-827b-f91ffa599e20 · inbound

Diagnosing and Improving Diffusion Models by Estimating the Optimal Loss Value cites this paper.

Diagnosing and Improving Diffusion Models by Estimating the Optimal Loss Value Fast Training of Diffusion Models with Masked Transformers

Reference 54

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arxiv_id, observed 2026-05-19T09:07:14.037023Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-19T09:05:58.516845Z digest=sha256:50901e761caa2368ca0a9079c5707573790b995e528b89dfed75b290255d3c11

Observation 13829bd9-c1ef-4d9a-b6d1-7032636d9a26 · inbound

Rethinking Discrete Tokens: Treating Them as Conditions for Continuous Autoregressive Image Synthesis cites this paper.

Rethinking Discrete Tokens: Treating Them as Conditions for Continuous Autoregressive Image Synthesis Fast Training of Diffusion Models with Masked Transformers

Reference 50

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:49:43.657417Z digest=sha256:ac965b784c313d27f5ddeccdceb30e10416d8f59f2d807fdc007e5aa094d371b

Observation 54f2b4ff-c8c9-4a47-9964-0a21b2e591d9 · inbound

MADI: Masking-Augmented Diffusion with Inference-Time Scaling for Visual Editing cites this paper.

MADI: Masking-Augmented Diffusion with Inference-Time Scaling for Visual Editing Fast Training of Diffusion Models with Masked Transformers

Reference 30

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no resolver link, observed 2026-08-06T16:48:34.038440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:48:34.038440Z digest=sha256:98b5ddf5efb60e21e8b2c8b583db3f81c5b9d936dc14005943915f669b2a35b8

Observation 1261d8e6-cabb-4627-a43f-00f83fb3e609 · inbound

Improving Joint Embedding Predictive Architecture with Diffusion Noise cites this paper.

Improving Joint Embedding Predictive Architecture with Diffusion Noise Fast Training of Diffusion Models with Masked Transformers

Reference 52

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no resolver link, observed 2026-08-06T15:44:53.604445Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:44:53.604445Z digest=sha256:d345943c26817c4579758edc44df03c4cb481518805a1bf1251173b7f63b9642

Observation 2b6ecdaa-0d4e-48e4-93fd-4e1daec5a277 · inbound

Missing Fine Details in Images: Last Seen in High Frequencies cites this paper.

Missing Fine Details in Images: Last Seen in High Frequencies Fast Training of Diffusion Models with Masked Transformers

Reference 64

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no resolver link, observed 2026-08-05T05:27:34.379629Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T05:27:34.379629Z digest=sha256:0d283802880114ca6bf5c16004ba786935839f2128a9351564ed6e9f19b25114

Observation fb61079b-6df8-4dd6-83f7-232c5fb4b940 · 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 Fast Training of Diffusion Models with Masked Transformers

Reference 25

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arxiv_id, observed 2026-05-18T05:22:23.937867Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-18T05:22:05.125849Z digest=sha256:623769512053c47c2efbb497d7fed6e5baa37ad13d0b14889b350d90bf533f01

Observation 7467a394-75b9-4e97-8669-c4ac14672611 · 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 Fast Training of Diffusion Models with Masked Transformers

Reference 80

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:35:00.843984Z digest=sha256:e084f24704c09a1cac8a557e5253bdef9ff0d9887deb21925c675e58e3acc6ee

Observation f37e1941-f099-465d-af4b-0c9760651f68 · inbound

MixFlow Training: Alleviating Exposure Bias with Slowed Interpolation Mixture cites this paper.

MixFlow Training: Alleviating Exposure Bias with Slowed Interpolation Mixture Fast Training of Diffusion Models with Masked Transformers

Reference 55

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no resolver link, observed 2026-08-03T14:53:03.638057Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:53:03.638057Z digest=sha256:34355771b30eea3ebea7c8727609a403cd53d75c34b772093587c8b3bec1fa70

Observation 65a1ecf4-f5d1-44c8-8569-7c0e8ee21e22 · inbound

Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation cites this paper.

Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation Fast Training of Diffusion Models with Masked Transformers

Reference 20

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arxiv_id, observed 2026-05-21T13:04:10.580837Z

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

source=pdf_text observed=2026-05-21T13:00:22.875471Z digest=sha256:1d7764a778525d5c1b27794a7934a0a8f51248032d55de81ab7ac86f2489e5b3

Observation 44f08017-9a0e-4aa1-964f-852df110be70 · inbound

Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation cites this paper.

Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers for Text-to-Image Generation Fast Training of Diffusion Models with Masked Transformers

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:50:47.050868Z digest=sha256:6b0bb3898978cbbde784ebee45d9ef778d5b13a6fd418aed7c497c542431fc57

Observation de8052a5-d3d6-4468-a7ba-8a3cf75730a6 · inbound

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders cites this paper.

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders Fast Training of Diffusion Models with Masked Transformers

Reference 26

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T01:25:20.415023Z digest=sha256:470adefcfbec3cf7b91ff44708da067592c9cacdeaed997c00a654b099b55c0c

Observation 3b2adf24-8812-4ff2-b41e-dccb7770bff9 · inbound

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

Data Warmup: Complexity-Aware Curricula for Efficient Diffusion Training Fast Training of Diffusion Models with Masked Transformers

Reference 38

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arxiv_id, observed 2026-05-10T23:40:54.141984Z

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

source=pdf_text observed=2026-05-10T18:55:26.852585Z digest=sha256:db7575d0aa8fe5780b9450478108177ebdb42806e0f359d47a7331281ac5e1ab

Observation de66bacb-14e1-44a3-93de-80c9b6cc2eef · inbound

ELT: Elastic Looped Transformers for Visual Generation cites this paper.

ELT: Elastic Looped Transformers for Visual Generation Fast Training of Diffusion Models with Masked Transformers

Reference 86

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arxiv_id, observed 2026-05-11T07:06:00.051356Z

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

source=pdf_text observed=2026-05-10T17:19:22.543462Z digest=sha256:499ee06f5a09b3d8da324c70bbacc49b310a69b473853db0c338369a1de6e2b3

Observation fb315d39-8a1f-4662-82e3-14adc4bb2564 · inbound

ELT: Elastic Looped Transformers for Visual Generation cites this paper.

ELT: Elastic Looped Transformers for Visual Generation Fast Training of Diffusion Models with Masked Transformers

Reference 82

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:35:03.444701Z digest=sha256:ce3862983369b1382c0f1206769bb627ca5a809698680962f2048c9c840cbf49

Observation c0344861-4a63-4bcb-b361-0d0ebe3e3b13 · inbound

Denoising, Fast and Slow: Difficulty-Aware Adaptive Sampling for Image Generation cites this paper.

Denoising, Fast and Slow: Difficulty-Aware Adaptive Sampling for Image Generation Fast Training of Diffusion Models with Masked Transformers

Reference 61

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arxiv_id, observed 2026-05-10T03:08:59.205615Z

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

source=pdf_text observed=2026-05-10T03:06:43.992858Z digest=sha256:7202493c79117a54f6fca0f4f5fa7e33e3a8f198ec1a6b171944a269785a832d

Observation cc77dfbe-21c3-4a73-8d4c-ff633c2d4d8c · inbound

End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer cites this paper.

End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer Fast Training of Diffusion Models with Masked Transformers

Reference 55

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arxiv_id, observed 2026-05-11T15:36:05.832440Z

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

source=pdf_text observed=2026-05-09T19:41:03.302303Z digest=sha256:53b12ba2a8b415894455b38599dcea2df2b2426a2c0615595d2e73a1d3e998b5

Observation 1dcca901-4945-4546-ad7f-bc3c9574ddbb · inbound

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

Elucidating Representation Degradation Problem in Diffusion Model Training Fast Training of Diffusion Models with Masked Transformers

Reference 64

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arxiv_id, observed 2026-05-12T06:36:26.415612Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-12T04:08:11.110912Z digest=sha256:02d3cb43ca4f088449737030a99a7e604da4e3b6b135b9a0d89432f0c9c50678

Observation 170e9b77-d498-4fb1-b5fb-6f73cdd884ec · 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 Fast Training of Diffusion Models with Masked Transformers

Reference 46

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arxiv_id, observed 2026-05-19T20:52:46.192834Z

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

source=pdf_text observed=2026-05-19T20:49:25.902880Z digest=sha256:bd521cb7524aa89c6c5f3445dc9b5cac72ebf9933bc3b80da19839e11cd844ff

Observation d1b7b837-8ef6-4925-b570-055f3e15fbde · inbound

FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion cites this paper.

FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion Fast Training of Diffusion Models with Masked Transformers

Reference 34

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arxiv_id, observed 2026-05-20T12:48:17.664054Z

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

source=pdf_text observed=2026-05-20T12:43:58.746650Z digest=sha256:32b3005dfc0c4c4636b3e6afdcc4659b463954140b4372cf223bba189f141703

Observation dd868de8-cddc-4767-8129-b14f1093c79e · inbound

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation cites this paper.

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation Fast Training of Diffusion Models with Masked Transformers

Reference 26

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arxiv_id, observed 2026-05-20T12:03:15.331324Z

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

source=pdf_text observed=2026-05-20T11:59:54.139888Z digest=sha256:cc37f0ae3e528c274ccc6bb10d861b1cc5727c54392b603bbbca01ae427b7156

Observation 2f3ca426-072d-4c4c-a7ab-f65a2a6395bb · inbound

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation cites this paper.

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation Fast Training of Diffusion Models with Masked Transformers

Reference 26

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arxiv_id, observed 2026-06-30T18:45:00.712640Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-30T18:39:40.667006Z digest=sha256:c7dfb3b0720f981904c1f2a3f7b7454519fd573a32c761f1420ebd8adbcad02d

Observation 921c3a4c-0e22-469e-a5d9-275bda7cbeb5 · inbound

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation cites this paper.

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation Fast Training of Diffusion Models with Masked Transformers

Reference 26

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no resolver link, observed 2026-08-02T13:49:19.876126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:49:19.876126Z digest=sha256:e85cf254c70f4ace4943d56d5d586a467f8d8c6e52d85fa4131f5dfcae3a447b

Observation 07539e4e-6a3f-4ae2-ae0c-00fbec1cf69b · inbound

Vision Foundation Models as Generalist Tokenizers for Image Generation cites this paper.

Vision Foundation Models as Generalist Tokenizers for Image Generation Fast Training of Diffusion Models with Masked Transformers

Reference 100

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arxiv_id, observed 2026-05-20T11:03:13.472208Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-20T11:01:24.738195Z digest=sha256:e095380387514c556729d38c61ec9bc51b48867e715e1cbd4b5d9432a5883a3e

Observation 4b08c0d9-0f40-4cfb-a1d4-0d27e8bca0dc · inbound

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

MaskAlign: Token-Subset Representation Alignment for Efficient Diffusion Training Fast Training of Diffusion Models with Masked Transformers

Reference 29

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verified exact
arxiv_id, observed 2026-07-02T22:37:26.196124Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-27T18:44:41.266768Z digest=sha256:cb252244cd5ec2770ee80a939029380dd98fe98f03788c518aff935d2cc4beb1

Observation 69277d24-07ac-4c3c-a60c-59bdb0c99a53 · inbound

IDEAL: In-DEpth ALignment Makes A Discrete Representation AutoEncoder cites this paper.

IDEAL: In-DEpth ALignment Makes A Discrete Representation AutoEncoder Fast Training of Diffusion Models with Masked Transformers

Reference 73

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metadata mismatch
arxiv_id, observed 2026-07-03T05:37:40.236125Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-27T13:10:14.308216Z digest=sha256:2ab83de2d760c98cf2f8c7d75165d31a9ccfdb705e3cbd55990239fcb255ded4

Observation cc6a1552-d762-46c7-b7f8-246ac4a4d2a5 · inbound

DiffusionBench: On Holistic Evaluation of Diffusion Transformers cites this paper.

DiffusionBench: On Holistic Evaluation of Diffusion Transformers Fast Training of Diffusion Models with Masked Transformers

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T16:59:57.979676Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-06-26T00:06:11.951205Z digest=sha256:a741fb1bee64aa9fc353bbafdda4a1c272a9edfdbd23c60ec93913446f2af525

Observation 46d55d90-dee0-4983-bb48-8d8908df0fa0 · inbound

PixelU: A U-Shaped Transformer for Efficient End-to-End Pixel Diffusion cites this paper.

PixelU: A U-Shaped Transformer for Efficient End-to-End Pixel Diffusion Fast Training of Diffusion Models with Masked Transformers

Reference 57

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T20:03:57.140969Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-29T04:31:57.169935Z digest=sha256:a62997126176390823c2d4bdd8766723ef220491e17e31383fc0e6381aa2413e

Observation 9b452c7b-b3c8-46d9-b918-b0a9efdb9971 · inbound

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

From SRA to Self-Flow: Data Augmentation or Self-Supervision? Fast Training of Diffusion Models with Masked Transformers

Reference 43

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T14:38:28.526783Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-07-03T14:36:59.833888Z digest=sha256:555f4c8e27ea4ce28ae8d16a4ddc96ef53c26817923fb02d846c74f1d6b8221f

Observation 51831a14-7900-4cd2-95da-7d1eb6f19e1f · inbound

DiverseDiT++: Quantifying, Analyzing, and Promoting Representation Diversity in Diffusion Transformers cites this paper.

DiverseDiT++: Quantifying, Analyzing, and Promoting Representation Diversity in Diffusion Transformers Fast Training of Diffusion Models with Masked Transformers

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-08T01:07:11.974745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T01:07:11.974745Z digest=sha256:4e6c9eede8ca21fd883d6f49539b8a0c4d5a7aa816e3b75bd9ce0b786ce1d8ad