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Paper Citation Record · LEDGER

D-AR: Diffusion via Autoregressive Models

As of 12 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 3 inbound Pith citation observations for arXiv:2505.23660.

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

pith.paper-citation-record.v1
2505.23660 v1

Coverage vector

measured 78 of 78 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:46:50.422272Z

measured 81 of 81 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:30:52.012479Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T15:46:47.760343Z

Reference resolution

78 of 78 outbound references displayed

  • verified exact0
  • verified fuzzy49
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cc2fd7a5-6935-4cb7-ae16-d3a166b29127 · outbound

This paper cites Gpt-4 technical report, 2024.

D-AR: Diffusion via Autoregressive Models Gpt-4 technical report, 2024

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0bdd1f13-bcc9-484c-b31d-0b763ef99acc · outbound

This paper cites Llama: Open and efficient foundation language models, 2023.

D-AR: Diffusion via Autoregressive Models Llama: Open and efficient foundation language models, 2023

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:58.156310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation c1eabaff-639f-404c-bdda-3a8602ee82a0 · outbound

This paper cites The llama 3 herd of models, 2024.

D-AR: Diffusion via Autoregressive Models The llama 3 herd of models, 2024

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:57.993686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 6ae694eb-0ca2-4ed6-8bef-2736a02a5103 · outbound

This paper cites Megatron-lm: Training multi-billion parameter language models using model parallelism, 2020.

D-AR: Diffusion via Autoregressive Models Megatron-lm: Training multi-billion parameter language models using model parallelism, 2020

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:57.837872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:45.047252Z digest=sha256:dea74759de913ca963111d24b45cdf705e8b287c33164a3863de22071357808f

Observation 1851360f-64dd-42bf-8ead-7a247658c9a8 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

D-AR: Diffusion via Autoregressive Models Efficient memory management for large language model serving with pagedattention

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:57.635380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:45.117742Z digest=sha256:a815ba6b4bed9c04dcf7aa04c7a3cc7f2cf5bff375fb978c1bac9cbed071f3f0

Observation 7b29db58-6dc8-4b5a-8b6b-6078c5f33cf3 · outbound

This paper cites Gonzalez, Clark W.

D-AR: Diffusion via Autoregressive Models Gonzalez, Clark W

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:57.456362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:45.192604Z digest=sha256:a2b374d9864f63a8e872cdd991feefc25b275527bd6780fb921750d0d31df32b

Observation f8e34a4b-1b1a-4a1f-8344-2307473f8521 · outbound

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

D-AR: Diffusion via Autoregressive Models Taming transformers for high-resolution image synthesis

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:57.257148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:45.267918Z digest=sha256:2d540ebcd11bb1952a73b185983cef522bac7c0d3300d397aafb9e10bd839e35

Observation 5f85896c-36cc-4baa-8d2d-c2ca345acda2 · outbound

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

D-AR: Diffusion via Autoregressive Models Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:45.345854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:45.345854Z digest=sha256:0928422f3f57235aec8df3aea66e9bcf0cf725d1d48224adb131e89c264d3e58

Observation 6fce79b7-7d9e-47f4-af21-3f66d28121c0 · outbound

This paper cites Autoregressive image generation using residual quantization.

D-AR: Diffusion via Autoregressive Models Autoregressive image generation using residual quantization

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:57.053333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:45.408223Z digest=sha256:3dae9eead574fadca5da2d7fecaec537e676c288b62bf806d9cc4d3008132a3e

Observation 5fc46b2b-5b37-4b57-9137-6ccfabae1046 · outbound

This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

D-AR: Diffusion via Autoregressive Models Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:45.483428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:45.483428Z digest=sha256:734515e1e6a3fd99a230ca4543113ca3f524018c4c768f80534ccd403e6f18db

Observation c64c6b9a-fb7b-41f6-8bb8-325a8e08c04c · outbound

This paper cites Transfusion: Predict the next token and diffuse images with one multi-modal model.

D-AR: Diffusion via Autoregressive Models Transfusion: Predict the next token and diffuse images with one multi-modal model

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:56.866677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:45.522286Z digest=sha256:6564de3971b9728429cd26889e9b70eca7eb24be6318bb0795fe409364b0232a

Observation ab56922a-5a01-478a-b2d4-753dda0fe3fd · outbound

This paper cites Show-o: One single transformer to unify multimodal understanding and generation.

D-AR: Diffusion via Autoregressive Models Show-o: One single transformer to unify multimodal understanding and generation

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:56.740306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:45.607014Z digest=sha256:d35a4123b059c981df4058375e6ae54d89a03e9f2ef3c2ce3023772dda75c892

Observation a3b50abb-d00b-48a1-ac98-81a0c90cbfbf · outbound

This paper cites JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation.

D-AR: Diffusion via Autoregressive Models JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:45.711461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:45.711461Z digest=sha256:031d5a443c87473450167e40e61a995a565667eeb8ecc45a6cb968f126b2165c

Observation d868a86c-bb90-42a5-b59e-7ee78d579020 · outbound

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

D-AR: Diffusion via Autoregressive Models Visual autoregressive modeling: Scalable image generation via next-scale prediction

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:56.641401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:45.815246Z digest=sha256:aa325e7784d7ead283222d1f9f34986a0650a678a73eff217f40360ed0f7d829

Observation b6155b4e-48df-4057-89c7-4ea9aa01895b · outbound

This paper cites RandAR: Decoder-only Autoregressive Visual Generation in Random Orders.

D-AR: Diffusion via Autoregressive Models RandAR: Decoder-only Autoregressive Visual Generation in Random Orders

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:45.910750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:45.910750Z digest=sha256:31f5b6e20bda72ca1aaf45f3ef376c677d052e32e03411fbf141160c66f8a883

Observation 4321cb41-7cef-4d38-a914-da9370c6a937 · outbound

This paper cites Randomized Autoregressive Visual Generation.

D-AR: Diffusion via Autoregressive Models Randomized Autoregressive Visual Generation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:46.010289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:46.010289Z digest=sha256:e814492a35b29b6bf81d8e2217c8c0e7fed8dc58fd6cdf914ac891a3597bc4b5

Observation a78fdd55-6a02-458b-82e4-efb16a63fd60 · outbound

This paper cites Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation.

D-AR: Diffusion via Autoregressive Models Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:46.106673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:46.106673Z digest=sha256:1cfca4ce074ff87a2a7ae1808d15e5965adf9cb6e23c74bc1e336a2fc1bb7e08

Observation 9f6f1c90-20f1-4684-8e28-cb9b1dacdf79 · outbound

This paper cites Imagefolder: Autoregressive image generation with folded tokens.

D-AR: Diffusion via Autoregressive Models Imagefolder: Autoregressive image generation with folded tokens

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:56.544284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.203180Z digest=sha256:86d279909976a13f7660df165e2e0c15f83b757e8c0b567de965667e0f32e225

Observation aa9c98c5-9106-4784-8def-9ecd3d449541 · outbound

This paper cites Denoising diffusion implicit models.

D-AR: Diffusion via Autoregressive Models Denoising diffusion implicit models

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:56.422149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.277161Z digest=sha256:d5493ae0d27978567401d8bd41d296dfbaa95eb445b64155a1682339775821f4

Observation e298f9e4-ab65-4006-9974-04b068b9c159 · outbound

This paper cites Denoising diffusion probabilistic models.

D-AR: Diffusion via Autoregressive Models Denoising diffusion probabilistic models

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:56.346787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.329003Z digest=sha256:0766075bd53b5ede224a1cc80fa104f2dacd31731f168a6a4f7a607cdf8cd4c7

Observation 3c83ddb2-574b-486c-a879-fed7cba23100 · outbound

This paper cites an unresolved cited work.

D-AR: Diffusion via Autoregressive Models Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:46:56.297325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.395827Z digest=sha256:29b975e6f70079e232f70170858d524c31ee4244502cab4c8ca292d8e6138e50

Observation a7da4bdc-df6e-49b0-a523-14ec3485ec94 · outbound

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

D-AR: Diffusion via Autoregressive Models Zero-shot text-to-image generation

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:56.201529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.429911Z digest=sha256:8aea0f684e2bf7f47895376941054a19b540f7adab7501903c02fa188844beb4

Observation 65f17faa-0034-4b6c-9cf7-56f00d57190c · outbound

This paper cites Flux.https://github.com/black-forest-labs/flux, 2023.

D-AR: Diffusion via Autoregressive Models Flux.https://github.com/black-forest-labs/flux, 2023

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:56.075666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.472756Z digest=sha256:a8e2620e00ef66b879827803bac7b3fcd56a5fd470aa63d8a1c0fbf8e433c3e6

Observation c80a2824-d562-4bda-950d-724c1e187904 · outbound

This paper cites SDXL: improving latent diffusion models for high-resolution image synthesis.

D-AR: Diffusion via Autoregressive Models SDXL: improving latent diffusion models for high-resolution image synthesis

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:55.977354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.542489Z digest=sha256:1475b4283391ed080c88630d142055377a6cdf0afaaa23b605df705b39ca8747

Observation 607903b1-6490-4556-988d-7e022317ba86 · outbound

This paper cites Generative modelling with inverse heat dissipation.

D-AR: Diffusion via Autoregressive Models Generative modelling with inverse heat dissipation

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:55.888345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.612055Z digest=sha256:82b32f593a6c75eae9b1cce3f67ec8269d8130eeef4f30506a92bb1fdc746a96

Observation 08767e9d-b55e-424a-9f43-b28360cb607f · outbound

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

D-AR: Diffusion via Autoregressive Models Imagenet: A large-scale hierarchical image database

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:55.776731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.678990Z digest=sha256:444ba65997c4fb9648fa606e389b30eff544e6367285a3c0789e210a87c164e7

Observation e8d0f683-9a73-4bbd-ae5d-a6bb4c2e194b · outbound

This paper cites Autoregressive image generation without vector quantization.

D-AR: Diffusion via Autoregressive Models Autoregressive image generation without vector quantization

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:55.651099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.740591Z digest=sha256:82327947896450e57d21a293fecb3e416096103f99575d52b44f35c496f71db5

Observation 81bce52c-9c4b-4281-bafd-ab8233fa9ba7 · outbound

This paper cites Causal Diffusion Transformers for Generative Modeling.

D-AR: Diffusion via Autoregressive Models Causal Diffusion Transformers for Generative Modeling

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:46.812359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:46.812359Z digest=sha256:1e5e91c1796f75648424466a4dcc7cf307c90f7361f1299cd1d8ed8350545ebc

Observation a8055208-63d7-4ffc-aaa9-a1946fc63dcf · outbound

This paper cites Diffusion forcing: Next-token prediction meets full-sequence diffusion.

D-AR: Diffusion via Autoregressive Models Diffusion forcing: Next-token prediction meets full-sequence diffusion

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:55.506216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.877496Z digest=sha256:65036e71c671e37a335745294db7e1fc40c6e3ee5a211d519b4a62f503db841c

Observation e0c9581b-8d86-4941-a926-74bf4f2de18a · outbound

This paper cites Denoising autoregressive transformers for scalable text-to-image generation.

D-AR: Diffusion via Autoregressive Models Denoising autoregressive transformers for scalable text-to-image generation

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:55.409488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:46.937239Z digest=sha256:25d5abf976db06b1d1ffeb274cac5accb346dcc314bd5a7093f3a9ef96078aad

Observation 5de7d2cc-1766-4fac-945b-7dc315b83c1d · outbound

This paper cites Dreamllm: Synergistic multimodal comprehension and creation.

D-AR: Diffusion via Autoregressive Models Dreamllm: Synergistic multimodal comprehension and creation

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:55.274802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:47.003626Z digest=sha256:c8a8f3183e7e3f9de9eab4aa05755dfc1b834cbf3dc755db385eedf39143d36d

Observation 29768e1e-5749-4550-b08f-3e954b42c2b7 · outbound

This paper cites SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation.

D-AR: Diffusion via Autoregressive Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:47.076151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:47.076151Z digest=sha256:a4efc8cbb91ab92f12330c646bcea54f60cc71f18eed03cde9dbc13a4f158a37

Observation 5627c6fb-d2e4-4660-a92d-6c1a2abf21d8 · outbound

This paper cites Next-gpt: Any-to-any multimodal llm.

D-AR: Diffusion via Autoregressive Models Next-gpt: Any-to-any multimodal llm

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:55.161398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:47.144507Z digest=sha256:ff3a609138f32e3b2a1f4cf70bf67db58b626809f7f2000c3ef4d261b4489b71

Observation 7eced1e8-7ed3-40a7-834e-8242f4958736 · outbound

This paper cites Transfer between Modalities with MetaQueries.

D-AR: Diffusion via Autoregressive Models Transfer between Modalities with MetaQueries

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:47.202196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:47.202196Z digest=sha256:c04948715d267548fd6c35007d8166e1ad5d0e8643bed9a2024924ff15f9e982

Observation d72283e4-28ef-4e34-a3d0-feddf376213a · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow.

D-AR: Diffusion via Autoregressive Models Flow straight and fast: Learning to generate and transfer data with rectified flow

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:55.044999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:47.282491Z digest=sha256:b542de4e323ffddf7227cc43b800010f0c16d6b3115bc837a963bdef65bfcd0f

Observation 95342513-c714-4ea1-8426-46851d6dfad0 · outbound

This paper cites Gemini: A family of highly capable multimodal models, 2025.

D-AR: Diffusion via Autoregressive Models Gemini: A family of highly capable multimodal models, 2025

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:54.891325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:47.356553Z digest=sha256:f361b97f668268c0a843dae574efaabf6d2dee01f3fe9862687b5803835936d9

Observation c867aadb-5927-4c46-9dc8-d14acb312c8c · outbound

This paper cites Qwen technical report, 2023.

D-AR: Diffusion via Autoregressive Models Qwen technical report, 2023

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:54.771591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:47.425911Z digest=sha256:a17f007d38970a4b1780e3c74eda6abb4671712bfcfa877e8b50e45bb22e5498

Observation 9ecfaeb2-d0e0-4cd1-81e5-b186005608ca · outbound

This paper cites Neural discrete representation learning.

D-AR: Diffusion via Autoregressive Models Neural discrete representation learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:54.606369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:47.477712Z digest=sha256:4419be611cff4e647e233878481c1c698a6280d88b96e4e083de87065c10a2b2

Observation fed357c7-d03f-43b7-b084-9698b3cea670 · outbound

This paper cites Long-Context Autoregressive Video Modeling with Next-Frame Prediction.

D-AR: Diffusion via Autoregressive Models Long-Context Autoregressive Video Modeling with Next-Frame Prediction

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:47.553558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:47.553558Z digest=sha256:c37b683df67cc4a326de20ee9fabe59089c206c0f60bbce27f30c20b8b1877d3

Observation 316ea204-d21e-4210-8d45-57ef8ba94ff0 · outbound

This paper cites Vector-quantized image modeling with improved VQGAN.

D-AR: Diffusion via Autoregressive Models Vector-quantized image modeling with improved VQGAN

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:54.455120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:47.605998Z digest=sha256:ccfc1cc2453b090abea2a68a693bea3666d6fb2823276ba3c59d424090532583

Observation 3e8f5478-5fd2-46c8-ae86-02e172096ec6 · outbound

This paper cites consistencydecoder.https://github.com/openai/consistencydecoder, 2023.

D-AR: Diffusion via Autoregressive Models consistencydecoder.https://github.com/openai/consistencydecoder, 2023

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:54.308521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:47.667123Z digest=sha256:fb156bee6de10ea642ff1d803020dd0439ea242870a3d58b8798663857aee605

Observation 29b6e9f4-6ec3-4d52-8b38-a40df98700e2 · outbound

This paper cites Epsilon-VAE: Denoising as Visual Decoding.

D-AR: Diffusion via Autoregressive Models Epsilon-VAE: Denoising as Visual Decoding

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:47.729995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:47.729995Z digest=sha256:9318efe5cca181478eecad69c5a7765baabcfa7e8ba7a18d8d6a9faa2d731d53

Observation 6b6c5137-aafc-4905-9915-c36de8743a07 · outbound

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

D-AR: Diffusion via Autoregressive Models HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:47.784895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:47.784895Z digest=sha256:47deae8d7b61cf0b37504e48da4933217b0d76ecea2c7f77cb6db26c78bc7e4b

Observation cca8bd1c-7bc7-40ba-8abd-4317c47d6275 · outbound

This paper cites Flow to the mode: Mode-seeking diffusion autoencoders for state-of-the-art image tokenization.arXiv, abs/2503.11056, 2025.

D-AR: Diffusion via Autoregressive Models Flow to the mode: Mode-seeking diffusion autoencoders for state-of-the-art image tokenization.arXiv, abs/2503.11056, 2025

Reference 44

Resolution
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no resolver link, observed 2026-08-07T12:46:47.839343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:47.839343Z digest=sha256:693e13c3d0438db705a1078c2147028208cd5a6f22597e8dcfcb43de57bda06e

Observation f9f6a167-692f-43c5-9e9b-258d056fdc24 · outbound

This paper cites Diffusion Autoencoders are Scalable Image Tokenizers.

D-AR: Diffusion via Autoregressive Models Diffusion Autoencoders are Scalable Image Tokenizers

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:47.896319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:47.896319Z digest=sha256:6eb0a1960e2b4728fb9ac3c0d10b74ed030378f638821b49ab7259c20a779a46

Observation 28319137-1daa-4ce8-ad0f-920983ee29a3 · outbound

This paper cites "Principal Components" Enable A New Language of Images.

D-AR: Diffusion via Autoregressive Models "Principal Components" Enable A New Language of Images

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:47.951311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:47.951311Z digest=sha256:29d100bc074d4c27c967f08f811341fa2f570995c45862d2943efcbfb3048181

Observation 325af286-6860-4494-83b2-e583c74728b9 · outbound

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

D-AR: Diffusion via Autoregressive Models FlexTok: Resampling Images into 1D Token Sequences of Flexible Length

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:47.998604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:47.998604Z digest=sha256:aad5b2caa4850291df9950e5a102865d3b5ea730ae4716bd4c8ec549c7712ba6

Observation 9934654c-9867-45f0-bfde-f83ad63e7a00 · outbound

This paper cites Kingma and Max Welling.

D-AR: Diffusion via Autoregressive Models Kingma and Max Welling

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:54.161492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.065178Z digest=sha256:ff5c637cdc61af29c89cdedd729abecf089a36addddb1ed796ea410c12d25369

Observation 6966e6d1-650c-4e97-aecc-be070dd3e8dc · outbound

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

D-AR: Diffusion via Autoregressive Models High-resolution image synthesis with latent diffusion models

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:53.985745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.126391Z digest=sha256:e64f2ab3d1b333f9873daebd2ca4791e62b245e19c77b142502ad5c653fef273

Observation 855a524b-5a6f-4049-9406-2c283f74792c · outbound

This paper cites Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens.

D-AR: Diffusion via Autoregressive Models Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:48.181078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:48.181078Z digest=sha256:b55606ec9698371360fd79edddf34b38431f5a89da3602c2c6623272c7f0e329

Observation 8879aa26-61a5-4ec0-9da7-ca1d08784bcc · outbound

This paper cites An image is worth 32 tokens for reconstruction and generation.Advances in Neural Information Processing Systems, 37:128940–128966, 2024.

D-AR: Diffusion via Autoregressive Models An image is worth 32 tokens for reconstruction and generation.Advances in Neural Information Processing Systems, 37:128940–128966, 2024

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:53.864890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.241560Z digest=sha256:c1fc4599e4d089c35a308f0ee6a68151ff92630d9a6ebf80102ab83fce5a4b49

Observation bba06e3a-0d78-4188-8753-832dc7b13fab · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

D-AR: Diffusion via Autoregressive Models Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:53.744013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.297165Z digest=sha256:b1eb88c8c9a60240d1d208df50df09f1af78a90c6a4191066b4e614a8bfa91cb

Observation 5385c25c-defb-4cd7-89d3-ed105ffad586 · outbound

This paper cites Scalable diffusion models with transformers.

D-AR: Diffusion via Autoregressive Models Scalable diffusion models with transformers

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:53.583535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.362277Z digest=sha256:ddc722ff33d8547a05de24fe970ba7b120ea2dd30c8952e7b4f42510a44a73bd

Observation 7d3a0bb2-49ad-405f-87f2-092907dfaa40 · outbound

This paper cites Albergo, Nicholas M.

D-AR: Diffusion via Autoregressive Models Albergo, Nicholas M

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:53.440867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.438333Z digest=sha256:c04941cfb273bb489882fb2c9e817c52e424ae0c3cc44f1ad7d643b517909b0f

Observation ae76940d-f15a-4eb2-a203-64cb01d7d059 · outbound

This paper cites Soda: Bottleneck diffusion models for representation learning.

D-AR: Diffusion via Autoregressive Models Soda: Bottleneck diffusion models for representation learning

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:53.302150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.493970Z digest=sha256:27ba1c88469b79f3616d8b0221df3dc6681eb02ba0c1d3cc436d76f45e26f190

Observation 76b2d064-cefe-479f-9802-f4884573b7dd · outbound

This paper cites Finite Scalar Quantization: VQ-VAE Made Simple.

D-AR: Diffusion via Autoregressive Models Finite Scalar Quantization: VQ-VAE Made Simple

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:48.586612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:48.586612Z digest=sha256:e1947ba6097b64e2016ec26fcc5715693213310f89896bbeadc15f02b4ac26e9

Observation 9bf76024-39b9-4abb-9a0d-a710eca451f5 · outbound

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

D-AR: Diffusion via Autoregressive Models Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:48.646407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:48.646407Z digest=sha256:a7acde2e4d9f0b7a1f191bfdb70e8325c4d799e9d17f275302cdf9dc84c530e8

Observation ff439393-75df-4481-ad94-fbde8cbe8c92 · outbound

This paper cites Courville.

D-AR: Diffusion via Autoregressive Models Courville

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:53.177354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.718076Z digest=sha256:84c1e9183374ab822ef1392c536b2af01401aec0caeda9939d821d2fb0a86aad

Observation fd52ed4f-e766-4136-b248-9e4b077a9001 · outbound

This paper cites simple diffusion: End-to-end diffusion for high resolution images.

D-AR: Diffusion via Autoregressive Models simple diffusion: End-to-end diffusion for high resolution images

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:53.024188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.808089Z digest=sha256:225fba04f0cc05ef2d2d6b4db0111ca0bf0a982dd4d7e1dfe3ae075328a53494

Observation 5372283d-689e-4f8b-bc24-59a8a11c1638 · outbound

This paper cites Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion.

D-AR: Diffusion via Autoregressive Models Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:48.877251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:48.877251Z digest=sha256:6831d4e87601f3a995fc501913b6efad061560021dd389554def0bcb1a9f7f0e

Observation 97779e07-a3b2-4fd9-8923-cc6859c5518d · outbound

This paper cites Efros, Eli Shechtman, and Oliver Wang.

D-AR: Diffusion via Autoregressive Models Efros, Eli Shechtman, and Oliver Wang

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:52.864653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:48.977094Z digest=sha256:81ccc6ca9b39128dad113e5f2fccfab039ad43244f2ce6510976c75940fe8daa

Observation 80d725be-ea0b-4133-a641-eae7ac0b35e8 · outbound

This paper cites Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think.

D-AR: Diffusion via Autoregressive Models Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:49.073670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:49.073670Z digest=sha256:7dd1c8b62627b8030fbb79b24c90950b1765893c39fd31e9d4feefdd1bdfa82c

Observation 46b4bd64-a50c-4d01-9915-319b3508432c · outbound

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

D-AR: Diffusion via Autoregressive Models Scaling rectified flow transformers for high-resolution image synthesis

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:52.695190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:49.162173Z digest=sha256:bd599b3262eba6c77488f5770c0b55ad4728d1db02b6772223fbcb9f69aaae11

Observation 687b383d-1854-4407-9eed-2dd2db344223 · outbound

This paper cites Classifier-Free Diffusion Guidance.

D-AR: Diffusion via Autoregressive Models Classifier-Free Diffusion Guidance

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:49.234889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:49.234889Z digest=sha256:c3cd24062704347f4c4f290a5b80221b8d6f82f02ec433a3ac4ea92fe43f72d5

Observation d863ca36-185a-41c7-a4eb-eae09dca3f1b · outbound

This paper cites Root mean square layer normalization.

D-AR: Diffusion via Autoregressive Models Root mean square layer normalization

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:52.519790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:49.328346Z digest=sha256:bc0d99e2c95de0f6331e8e554868a3bb49d33cb138f52e489ccd18b44daf1fde

Observation 3305620b-3e66-49d0-b7d0-cf7a90c8bd08 · outbound

This paper cites GLU Variants Improve Transformer.

D-AR: Diffusion via Autoregressive Models GLU Variants Improve Transformer

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:49.393422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:49.393422Z digest=sha256:e2b482467224dba1fa56f30b5540ab2699669701764e9e78d25466148e7326ed

Observation bc4ebb81-7754-4ea1-8188-7201e12cb79c · outbound

This paper cites an unresolved cited work.

D-AR: Diffusion via Autoregressive Models Unresolved cited work

Reference 67

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:46:52.351782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:49.496155Z digest=sha256:66fa31f12ba56dd5ce947028a641aeae84f457ae93eab7e8be8907a5109ae753

Observation 6368fa96-e6dc-4ac5-b6fe-cfa727010e68 · outbound

This paper cites Kingma and Jimmy Ba.

D-AR: Diffusion via Autoregressive Models Kingma and Jimmy Ba

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:52.204911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:49.589964Z digest=sha256:82d5d1b7b664a5ba2cbd071c0e5610867425138bdcb343c839b70642d6a5a846

Observation 0f1ac33e-816f-4432-a5b5-b9c28b561e86 · outbound

This paper cites Decoupled Weight Decay Regularization.

D-AR: Diffusion via Autoregressive Models Decoupled Weight Decay Regularization

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:49.660399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:49.660399Z digest=sha256:26f4d7936afeda516a48756fe487fdd78f40e5af8ff487602431512510b9d743

Observation cff7d735-a358-4a25-9363-bd122bb32b7a · outbound

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

D-AR: Diffusion via Autoregressive Models Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:52.046547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:49.766127Z digest=sha256:98a9f4fe469481d996aaa1f3b4d2af702f4d7b5d91fbd2e59849af06ccf93485

Observation 7288a251-59ad-46cc-a52b-2766905c1ca9 · outbound

This paper cites Improved techniques for training gans.Advances in neural information processing systems, 29, 2016.

D-AR: Diffusion via Autoregressive Models Improved techniques for training gans.Advances in neural information processing systems, 29, 2016

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:49.846399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:49.846399Z digest=sha256:0594caad298fab53e1b6a4b35704313347086bdda79c33034524c6afed45aa8b

Observation 43d01ad3-7397-4900-9ab6-b8e9019691a2 · outbound

This paper cites Diffusion models beat gans on image synthesis.

D-AR: Diffusion via Autoregressive Models Diffusion models beat gans on image synthesis

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:51.877309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:49.923905Z digest=sha256:b6663f6e7b0d7a3458132f4bca7ff20800cd2b0b884d04b85bce5089c07310ac

Observation a8af3289-c862-4f5b-9275-f24204b80e62 · outbound

This paper cites With an Explanation of the Method of Integration Employed in Constructing the Tables Which Give the Theoretical Forms of Such Drops.

D-AR: Diffusion via Autoregressive Models With an Explanation of the Method of Integration Employed in Constructing the Tables Which Give the Theoretical Forms of Such Drops

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:51.734187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:50.002950Z digest=sha256:bf5155bc9ae2f1710b4bc475ac30f3136d0b72e7764f035b618438cc98e6ca9d

Observation 1bc34565-56ec-4936-929c-50fdf2b5c808 · outbound

This paper cites an unresolved cited work.

D-AR: Diffusion via Autoregressive Models Unresolved cited work

Reference 74

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:46:51.581439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1ca93848-08df-464a-a1ef-b0d7cee22c3b · outbound

This paper cites Scalable image tokenization with index backpropagation quantization.arXiv, 2024.

D-AR: Diffusion via Autoregressive Models Scalable image tokenization with index backpropagation quantization.arXiv, 2024

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:51.432509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:50.178482Z digest=sha256:34fcf3d48a9084f3ac13f7d8ef836e14c578edd4e8dabb8a21125be8dc069cc4

Observation c8d65a22-8cc1-4505-953d-979ad1703584 · outbound

This paper cites Layer Normalization.

D-AR: Diffusion via Autoregressive Models Layer Normalization

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:50.265973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:50.265973Z digest=sha256:b41ac74dad39965bbbd4926e1c9ef6e9a65ff478fed3046b671332de3237b3ec

Observation d5bca98a-29ab-4de7-9040-623c354f0860 · outbound

This paper cites Sigmoid-weighted linear units for neural network function approximation in reinforcement learning.Neural Networks, 107:3–11, 2018.

D-AR: Diffusion via Autoregressive Models Sigmoid-weighted linear units for neural network function approximation in reinforcement learning.Neural Networks, 107:3–11, 2018

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:51.285726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 9ec4b6cb-412a-4de5-a580-0ff4622bf5a4 · outbound

This paper cites Query-key normaliza- tion for transformers.

D-AR: Diffusion via Autoregressive Models Query-key normaliza- tion for transformers

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:46:51.108689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:46:50.422272Z digest=sha256:007e8d43a442275a83abba2728c2b7aea1df082f741492362dd9b69bba2c961d

Pith citing papers

Observation 961b28fe-e711-4f17-aec5-53c66f4178aa · inbound

EndoCoT: Scaling Endogenous Chain-of-Thought Reasoning in Diffusion Models cites this paper.

EndoCoT: Scaling Endogenous Chain-of-Thought Reasoning in Diffusion Models D-AR: Diffusion via Autoregressive Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-14T22:25:04.080629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T22:25:04.080629Z digest=sha256:64618c37ee1032d55bdb45d2b8fe3ae6380040d69c49073ee1ef872988705ab6

Observation e2cea1fd-b2c2-48a6-beb6-07a389a3d921 · inbound

Fast Text-to-Audio Generation with One-Step Sampling via Energy-Scoring and Auxiliary Contextual Representation Distillation cites this paper.

Fast Text-to-Audio Generation with One-Step Sampling via Energy-Scoring and Auxiliary Contextual Representation Distillation D-AR: Diffusion via Autoregressive Models

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:46:47.878360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-09T19:17:09.247932Z digest=sha256:2bdb94a3d924a9d3fa4ca77d42f5142ecc74330c595201cabf66e95bc3b7d88d

Observation 01cdc37b-c3df-44f3-bade-2ce3d50209b4 · inbound

Learning to Tessellate: Point Cloud Generation via Recursive Spectral Partitioning cites this paper.

Learning to Tessellate: Point Cloud Generation via Recursive Spectral Partitioning D-AR: Diffusion via Autoregressive Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T07:30:52.012479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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