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Paper Citation Record · LEDGER

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer

As of 8 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 1 inbound Pith citation observation for arXiv:2507.04947.

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

pith.paper-citation-record.v1
2507.04947 v1

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:41:23.831463Z

measured 76 of 76 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T04:23:08.137866Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T04:23:09.921374Z

Reference resolution

75 of 75 outbound references displayed

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  • verified fuzzy30
  • unresolved45
  • parse uncertain0
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External citation measurements

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Outbound references

Observation 34dd3310-39fe-4f53-a573-f35974eb1cd1 · outbound

This paper cites FlexTok: Resampling Images into 1D Token Sequences of Flexible Length.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer FlexTok: Resampling Images into 1D Token Sequences of Flexible Length

Reference 1

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Observation 12388c83-15cb-42a7-aad7-f388b1f89336 · outbound

This paper cites Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis

Reference 2

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Observation b34dd59c-ddf7-498e-8ecd-29082de15795 · outbound

This paper cites All are worth words: A vit backbone for diffusion models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer All are worth words: A vit backbone for diffusion models

Reference 3

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Observation 1b725b72-339a-46c0-8f26-3a378878204c · outbound

This paper cites Flux, 2024.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Flux, 2024

Reference 4

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Observation 4cec7b2a-686c-4369-a2fd-a9e758073b30 · outbound

This paper cites Efficientvit: Lightweight multi-scale attention for high- resolution dense prediction.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Efficientvit: Lightweight multi-scale attention for high- resolution dense prediction

Reference 5

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Observation 745ad257-39eb-4eba-aade-9af00a02f3e0 · outbound

This paper cites Condition-aware neural network for controlled image generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Condition-aware neural network for controlled image generation

Reference 6

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Observation 047dad19-1554-4487-9528-3b8954e7e9d6 · outbound

This paper cites Maskgit: Masked generative image transformer.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Maskgit: Masked generative image transformer

Reference 7

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source=pdf_text observed=2026-08-06T19:41:23.617922Z digest=sha256:1468d2830df93227d3ee0463216c107fa43db834d4d2ab04021a3ed6ef00eca2

Observation 0757d32b-5882-4aac-a7ab-e83195aef7f6 · outbound

This paper cites Muse: Text-To-Image Generation via Masked Generative Transformers.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Muse: Text-To-Image Generation via Masked Generative Transformers

Reference 8

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source=pdf_text observed=2026-08-06T19:41:23.621281Z digest=sha256:a2354121a9369d3b06df7b8348166794183f195a344e756dd8e783875df05a49

Observation 62f40565-28e3-4d95-bbfe-fa5f79d53533 · outbound

This paper cites SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer

Reference 9

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source=pdf_text observed=2026-08-06T19:41:23.624757Z digest=sha256:d6b869f6f0a7a13bc8a12853e772d8347e3a03fe9d6ab132fee30bc1b7f1c4eb

Observation 137e2f05-51d3-4712-84a0-7b96c1511d17 · outbound

This paper cites Masked Autoencoders Are Effective Tokenizers for Diffusion Models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Masked Autoencoders Are Effective Tokenizers for Diffusion Models

Reference 10

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Observation a32b09d4-4e31-4bb0-b5a3-beb141350c54 · outbound

This paper cites Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models

Reference 11

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Observation 4ba7edef-3ab1-4b73-a8ab-98746842fe2c · outbound

This paper cites Pixart- σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Pixart- σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation

Reference 12

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Observation 1ccf0a15-739d-47c5-9915-32ae42beb7c9 · outbound

This paper cites PIXART-{\delta}: Fast and Controllable Image Generation with Latent Consistency Models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer PIXART-{\delta}: Fast and Controllable Image Generation with Latent Consistency Models

Reference 13

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Observation 7f6b40b9-ce03-41c3-9da7-c0df6c9da372 · outbound

This paper cites Pixart- α: Fast training of diffusion transformer for photorealistic text-to-image synthesis.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Pixart- α: Fast training of diffusion transformer for photorealistic text-to-image synthesis

Reference 14

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source=pdf_text observed=2026-08-06T19:41:23.641117Z digest=sha256:58198fc3fb09dd75a238eb0c98db6ae0a622b78b95f77126f82b82e0f23f1fea

Observation e8a436c8-2254-4d9e-92f2-2f1249cd3316 · outbound

This paper cites MaskMamba: A Hybrid Mamba-Transformer Model for Masked Image Generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer MaskMamba: A Hybrid Mamba-Transformer Model for Masked Image Generation

Reference 15

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Observation db8be56c-dd30-42d4-8ed1-30208cf160cb · outbound

This paper cites Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling

Reference 16

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Observation f3f8b3ac-f320-46cd-8758-8e241995f1bb · outbound

This paper cites Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient

Reference 17

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Observation 1905c30c-1215-4bfb-b4ec-04f85879daa4 · outbound

This paper cites Vqgan-clip: Open domain image generation and editing with natural language guidance.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Vqgan-clip: Open domain image generation and editing with natural language guidance

Reference 18

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Observation 2e503436-5d51-4628-b25e-9fff171b8223 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Imagenet: A large-scale hierarchical image database

Reference 19

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Observation 3dc5b9e6-e0b5-4149-b72d-e91cbb5a07dd · outbound

This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Bert: Pre-training of deep bidirectional trans- formers for language understanding

Reference 20

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Observation b26dfbd7-02f7-408d-a6c8-daa19cfa3668 · outbound

This paper cites Cogview: Mastering text-to-image generation via transformers.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Cogview: Mastering text-to-image generation via transformers

Reference 21

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Observation ed0c676b-6098-46ad-aa37-1aa6ec6573e9 · outbound

This paper cites Cogview2: Faster and better text-to-image generation via hierarchical transformers.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Cogview2: Faster and better text-to-image generation via hierarchical transformers

Reference 22

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Observation bf37ec64-e006-42f6-a2c2-d3cb9b640474 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Taming transformers for high-resolution image synthesis

Reference 23

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Observation bd3707a4-1393-4e79-a4a8-870fe9598436 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 24

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Observation ff003569-80a0-4a66-a324-9c1a05f1c1a9 · outbound

This paper cites Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens

Reference 25

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Observation 5cbe8f3e-1ded-4354-af83-b2672b2a4d1d · outbound

This paper cites Make-a-scene: Scene- based text-to-image generation with human priors.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Make-a-scene: Scene- based text-to-image generation with human priors

Reference 26

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Observation 02221b71-5d38-4501-90ea-30a1900a85e3 · outbound

This paper cites Geneval: An object-focused framework for evaluating text- to-image alignment.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Geneval: An object-focused framework for evaluating text- to-image alignment

Reference 27

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source=pdf_text observed=2026-08-06T19:41:23.680293Z digest=sha256:b2fd944e41f1f6b5a57330b55dd4d7ec8ba30df1f9f05f0d5a50481f8f516325

Observation 4ad5d9f1-7fac-4d07-8739-4632c1a45992 · outbound

This paper cites Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis

Reference 28

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Observation 188553c7-4b49-4eb3-a5f5-8047a6497060 · outbound

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

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 29

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Observation 7737570e-471b-4ad9-8965-39b0e94ec915 · outbound

This paper cites LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding

Reference 30

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Observation 60d468d8-6607-4641-8640-b7445fdc2ca0 · outbound

This paper cites Democratizing Text-to-Image Masked Generative Models with Compact Text-Aware One-Dimensional Tokens.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Democratizing Text-to-Image Masked Generative Models with Compact Text-Aware One-Dimensional Tokens

Reference 31

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Observation 14c41753-a012-4487-a846-551f7d8cc919 · outbound

This paper cites Videopoet: A large language model for zero-shot video gen- eration.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Videopoet: A large language model for zero-shot video gen- eration

Reference 32

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source=pdf_text observed=2026-08-06T19:41:23.694896Z digest=sha256:ac3723ae19418ea4debf42363cb05dc210bd2c14503b324563a4efbdcb09711f

Observation ad64d74f-3a96-4457-af1b-4ad3542c923a · outbound

This paper cites Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation

Reference 33

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Observation d018cac0-b23c-4277-9dc4-1541957b1376 · outbound

This paper cites Mage: Masked generative encoder to unify representation learning and image synthe- sis.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Mage: Masked generative encoder to unify representation learning and image synthe- sis

Reference 34

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Observation 6b558d4a-4b2c-4a46-acf1-1aa8dd686bf9 · outbound

This paper cites Autoregressive image generation without vec- tor quantization.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Autoregressive image generation without vec- tor quantization

Reference 35

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:41:23.704341Z digest=sha256:759d4ecfc7e35e1354467f146d6d8f3fc31398b9616f4d3bb1a5fad6b715fc1b

Observation da46fd01-6f63-4522-9731-2f592007beca · outbound

This paper cites ControlVAR: Exploring Controllable Visual Autoregressive Modeling.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer ControlVAR: Exploring Controllable Visual Autoregressive Modeling

Reference 36

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source=pdf_text observed=2026-08-06T19:41:23.707412Z digest=sha256:3b48af054c64a411959fe482187ada4fe94e0f1b2e3357d13ee99a9b9b5309ea

Observation 61176306-b6d5-4f11-adea-42bbed8557de · outbound

This paper cites Vila: On pre-training for vi- sual language models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Vila: On pre-training for vi- sual language models

Reference 37

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:41:23.710603Z digest=sha256:2785795ffa5a8671346951bdd3126fd635d71136d5a905bcb1f8fc3dec477a0f

Observation 7a3d0dcb-6129-494c-8159-78cd2e95eefa · outbound

This paper cites Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Playground v3: Improving Text-to-Image Alignment with Deep-Fusion Large Language Models

Reference 38

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source=pdf_text observed=2026-08-06T19:41:23.713635Z digest=sha256:2bb5c11abdfc0be63658feaab37a2664668d45ac19b6bf4a205c5fded2c93ae7

Observation d2bd89df-c72d-4e5d-8a5c-2f7b2e9f196a · outbound

This paper cites Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining

Reference 39

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source=pdf_text observed=2026-08-06T19:41:23.716761Z digest=sha256:fecfd3d2f0c7173399d91307ab684648aafab172e4972a36624e62a8219a409e

Observation 10e17c38-ac4e-4510-a198-8794726844f2 · outbound

This paper cites World Model on Million-Length Video And Language With Blockwise RingAttention.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer World Model on Million-Length Video And Language With Blockwise RingAttention

Reference 40

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source=pdf_text observed=2026-08-06T19:41:23.720034Z digest=sha256:9439135f1a8d2ab716076b7e0d3faf12b71480c023ffae4a9051b38b35708f0e

Observation 05608fb7-ecfb-41a0-b473-66459712bb50 · outbound

This paper cites Exploring the role of large language models in prompt encoding for diffusion models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Exploring the role of large language models in prompt encoding for diffusion models

Reference 41

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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=2026-08-06T19:41:23.723272Z digest=sha256:487d32eafd87ce8f9da9043a2b90352ebdb23c94c060f2790eac21ac4ad53b09

Observation 217bf85a-1191-4a80-8f3b-3e43d2497ea0 · outbound

This paper cites STAR: Scale-wise Text-conditioned AutoRegressive image generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer STAR: Scale-wise Text-conditioned AutoRegressive image generation

Reference 42

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source=pdf_text observed=2026-08-06T19:41:23.726623Z digest=sha256:5e482f62e319acc59a0944e229ebcaf772509a95de981b9a710adb243a61377b

Observation 3a459c38-41de-4b25-bb4f-1463c15ff854 · outbound

This paper cites Hello gpt-4o, 2024.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Hello gpt-4o, 2024

Reference 43

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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=2026-08-06T19:41:23.729953Z digest=sha256:0b2c353a9563fa0ab763e572981971c34f85cdc854fd00b9426615cf7f8c873e

Observation e70fe837-c7d5-4f4b-b432-cad4b1270b93 · outbound

This paper cites Scalable diffusion models with transformers.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Scalable diffusion models with transformers

Reference 44

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source=pdf_text observed=2026-08-06T19:41:23.732818Z digest=sha256:aaf7dee8e8c09b2f9d0588fd8a26848dfff195ffef0c2b0fa59c6743160025fd

Observation d32be879-4738-4d53-8d2a-1f2e9962b981 · outbound

This paper cites W ¨urstchen: An ef- ficient architecture for large-scale text-to-image diffusion models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer W ¨urstchen: An ef- ficient architecture for large-scale text-to-image diffusion models

Reference 45

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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=2026-08-06T19:41:23.736414Z digest=sha256:ac15da00b8a6cc95de67b745be7a4b0a0255875c215085be3f270d2ebe1a2313

Observation 387bf42c-f125-42aa-942a-126750c839f8 · outbound

This paper cites Sdxl: Improving latent diffusion models for high-resolution image synthesis.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Sdxl: Improving latent diffusion models for high-resolution image synthesis

Reference 46

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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=2026-08-06T19:41:23.740004Z digest=sha256:42c1c0900e210952483230efbcec1563f6ddbcc517357286b1ffcf9dcab74a72

Observation e77a85cc-3c45-4774-b6cd-e6648a3feeb8 · outbound

This paper cites TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 47

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source=pdf_text observed=2026-08-06T19:41:23.743296Z digest=sha256:b15f084759386a6b71e70cfb86a537824ae33a32f975bcb9f1ef72753ff98678

Observation 96036b35-5845-4c61-89e6-8ba9814ae24e · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 48

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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=2026-08-06T19:41:23.746402Z digest=sha256:76ba606674cf9cdb1d8eff036aaf5961e9e8fea391d9fc5012bb14b1068ae5c9

Observation 514fabfe-dc50-4fb9-8220-db01381d887b · outbound

This paper cites Zero-shot text-to-image generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Zero-shot text-to-image generation

Reference 49

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source=pdf_text observed=2026-08-06T19:41:23.749368Z digest=sha256:bc96f52ce44b751706faf9fb68a90030a00d4118eba7b5fdb1dd0ee77cb268e1

Observation b59c94d5-6f14-4b37-a016-3c49affc816d · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer High-resolution image synthesis with latent diffusion models

Reference 50

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source=pdf_text observed=2026-08-06T19:41:23.752473Z digest=sha256:d572e0ae484317c9417b64d49f6468c03777c4f947cc029b93eab125e2b8cf2a

Observation 98a0a5e4-7bc7-4417-86af-e1c317274499 · outbound

This paper cites Journeydb: A benchmark for generative im- age understanding.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Journeydb: A benchmark for generative im- age understanding

Reference 51

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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=2026-08-06T19:41:23.755319Z digest=sha256:ff82fd1db62f70f0a6ef8aa8e270f75e9f7d1e0475d55bfc4c6469d67b6de624

Observation b3db0879-fb1b-466e-8256-142c6ec613f1 · outbound

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

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 52

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source=pdf_text observed=2026-08-06T19:41:23.758914Z digest=sha256:d1a666e161688fc93b8bd2907103bb0f4715c2ceb7d417dca158e22c898c76d8

Observation 32ffb138-09c0-44ba-ae2e-ee0063776e3d · outbound

This paper cites HART: Efficient Visual Generation with Hybrid Autoregressive Transformer.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

Reference 53

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source=pdf_text observed=2026-08-06T19:41:23.762860Z digest=sha256:ff35f9ceb6327bcc77ffe88b350c5d538b747e41cf254fc8d59ea2db85d2bfb2

Observation ef40a9a9-7bfc-4dea-91d1-b34525e77634 · outbound

This paper cites Introducing auraflow v0.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Introducing auraflow v0

Reference 54

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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=2026-08-06T19:41:23.766316Z digest=sha256:e9865872000e263afed8dec268cb0e43199f730b7166adc72f8b1697c383581d

Observation ea4877f2-701f-4f21-a926-cce601e32e35 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Gemini: A Family of Highly Capable Multimodal Models

Reference 55

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source=pdf_text observed=2026-08-06T19:41:23.769261Z digest=sha256:1a5d35c96244a2002fbef3ffc83b7c4a0deb7d7ea45ebfe4ec33a4b21cf231d1

Observation 05c6b64d-7efb-40a4-b309-aa4736357ae1 · outbound

This paper cites Kolors: Effective training of diffusion model for photorealistic text-to-image synthesis.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Kolors: Effective training of diffusion model for photorealistic text-to-image synthesis

Reference 56

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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=2026-08-06T19:41:23.772210Z digest=sha256:a39473acbfd33a63b603b655fa12b330d98a1904df58d28aef16ec5dc73c541a

Observation 47186ff9-ba17-4818-a852-85093f69afeb · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Visual autoregressive modeling: Scalable image generation via next-scale prediction

Reference 57

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:41:23.775229Z digest=sha256:a88b5bd007090297b597a844a24261132dd0368e703303c874db36a0455696f5

Observation 24ca1245-6f49-4bc6-8998-30b18845bdf7 · outbound

This paper cites Neural discrete representation learning.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Neural discrete representation learning

Reference 58

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source=pdf_text observed=2026-08-06T19:41:23.778537Z digest=sha256:a1881fa0842a415811db5bfc66c131df58d0d57039bb7bffe17c3f9c7e035f22

Observation e18e3c3e-01c1-45dd-a062-775cf528945c · outbound

This paper cites Phenaki: Variable Length Video Generation From Open Domain Textual Description.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Phenaki: Variable Length Video Generation From Open Domain Textual Description

Reference 59

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source=pdf_text observed=2026-08-06T19:41:23.781644Z digest=sha256:9ff5d2cef2b85fd7fdf4ac7689766cb778deb483c457abda6959516c646e28fb

Observation 9b48ac4f-56d7-4001-9c42-9910aba55a29 · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Emu3: Next-Token Prediction is All You Need

Reference 60

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source=pdf_text observed=2026-08-06T19:41:23.784989Z digest=sha256:97940e286b665390a4128743dcf516d12724d24fa1dc9f660a941a1301ee71c7

Observation aeb2ad6d-4043-4c25-9816-35067e89fed0 · outbound

This paper cites Parallelized Autoregressive Visual Generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Parallelized Autoregressive Visual Generation

Reference 61

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source=pdf_text observed=2026-08-06T19:41:23.788082Z digest=sha256:60d9b0e04b486b1dbfb08a5cf894123ae606ef6d8fde1e613808b4e5eafad017

Observation 10e389e7-0f61-43f6-b4b9-303926d15be5 · outbound

This paper cites Maskbit: Embedding-free image generation via bit tokens.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Maskbit: Embedding-free image generation via bit tokens

Reference 62

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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=2026-08-06T19:41:23.791122Z digest=sha256:f724a6cb10dcaf81e7fd1ac242db3fca9a27f02a490104fa16b951ec8c19c848

Observation b6830a1d-9454-4d9e-9dc4-fdfa04d5e7f3 · outbound

This paper cites Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation

Reference 63

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source=pdf_text observed=2026-08-06T19:41:23.793876Z digest=sha256:9894a76162c220fbc61101756c68306cf3df9d0abd38c41a8baef470fc75476b

Observation 6d49930b-816d-492d-a59a-bb82a5337018 · outbound

This paper cites VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation

Reference 64

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T19:41:23.796917Z digest=sha256:724665adb9fb4f41581345e3455fb55964b5f7fac178551773c12b2ac3f66065

Observation 3a94fa02-2984-48fc-8485-0a6fe88377f3 · outbound

This paper cites SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

Reference 65

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source=pdf_text observed=2026-08-06T19:41:23.799913Z digest=sha256:71be0ec8e99ef1f99d785fae9aef2c549d53ef22d01731e34f2806b721226c1d

Observation 17170477-082e-4982-9a7a-c920950cf2bd · outbound

This paper cites SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer

Reference 66

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source=pdf_text observed=2026-08-06T19:41:23.803601Z digest=sha256:39a9e76dc06c5b1c3956b5fec5b3022b84df9a088670ccf0c9db6a189781bc26

Observation 7d9a9c8d-afb2-4b25-9f0c-0017bc5bd809 · outbound

This paper cites Show-o: One Single Transformer to Unify Multimodal Understanding and Generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 67

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source=pdf_text observed=2026-08-06T19:41:23.806841Z digest=sha256:70c91a94f3881b2e1fc04e8c5c89552b93eff0c2994376f2be3e242d38f26a11

Observation 7220a54c-9e3d-467b-bfcd-98c904db1064 · outbound

This paper cites CAR: Controllable Autoregressive Modeling for Visual Generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer CAR: Controllable Autoregressive Modeling for Visual Generation

Reference 68

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source=pdf_text observed=2026-08-06T19:41:23.810106Z digest=sha256:cad984d6f27eac5a45556396cad4bbd2d512b7e7a637c13c487a9e8f3211c005

Observation 9d469825-40e3-496d-81ae-64fe1f51a583 · outbound

This paper cites Scaling autoregres- sive models for content-rich text-to-image generation.Trans.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Scaling autoregres- sive models for content-rich text-to-image generation.Trans

Reference 69

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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=2026-08-06T19:41:23.813094Z digest=sha256:2234af03dcbfe9c3a2604c25160f7edd9de2f77027dd85d753fba2d6cb6248e6

Observation a4399186-bebf-4829-8b73-eacedc0fa28e · outbound

This paper cites Magvit: Masked generative video transformer.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Magvit: Masked generative video transformer

Reference 70

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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=2026-08-06T19:41:23.816090Z digest=sha256:4c9b2b52fc0620998d2e657c3bfc143b1492f9be4bc03a1520a42269f7ae5927

Observation 852f6685-331f-4262-8912-dd1508fe325f · outbound

This paper cites An image is worth 32 tokens for reconstruction and generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer An image is worth 32 tokens for reconstruction and generation

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:41:24.226993Z

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=2026-08-06T19:41:23.818931Z digest=sha256:e6f4ac64180f8803bbfabd8e0004c0d78778434e30746b623a52977d3d252a18

Observation 0cbbcf26-880c-45f5-b390-3b08383a86aa · outbound

This paper cites ShieldGemma: Generative AI Content Moderation Based on Gemma.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer ShieldGemma: Generative AI Content Moderation Based on Gemma

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-06T19:41:23.821729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:41:23.821729Z digest=sha256:b5e86d79ad4fdf1f4041aac8e395c4cdde5997d2064730ddfc3004684eed3bb6

Observation 04a282f2-e224-4651-b17e-bd2a670c7af5 · outbound

This paper cites Language-Guided Image Tokenization for Generation.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer Language-Guided Image Tokenization for Generation

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-06T19:41:23.825012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:41:23.825012Z digest=sha256:3943c5c7d9ffe5768cacdbe7e2aa38b2416298381e7cf0f90da0b8cf30cf5929

Observation 43ad1ff8-72f0-4a82-99e6-2f3e1f952c7e · outbound

This paper cites VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-06T19:41:23.828655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:41:23.828655Z digest=sha256:da91c05c4c48d77ba0a4c7b841b5ab1d71ecc7332ad51fa0f37e98b3c522ec5a

Observation 6b79ced7-fa55-4df9-a90c-e187a0b47102 · outbound

This paper cites A red heart.

DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer A red heart

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:41:24.215300Z

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=2026-08-06T19:41:23.831463Z digest=sha256:7809640edfc8cfee1f56378f0740ed7e0d9c018b8a321d6ba829ff17717dcfc5

Pith citing papers

Observation 70406000-a5b0-4912-b562-5cf97973bb31 · inbound

HPSv3: Towards Wide-Spectrum Human Preference Score cites this paper.

HPSv3: Towards Wide-Spectrum Human Preference Score DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-06T04:23:09.993343Z

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=2026-08-06T04:23:08.137866Z digest=sha256:62a6c5e2a19ee79050f4783aab69ab19719b85b97817901be25fe15c6366a283