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Paper Citation Record · LEDGER

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention

As of 12 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 1 inbound Pith citation observation for arXiv:2510.16325.

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

pith.paper-citation-record.v1
2510.16325 v4

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:20:08.241880Z

measured 23 of 23 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T14:40:20.517450Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T14:43:22.566970Z

Reference resolution

22 of 22 outbound references displayed

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External citation measurements

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Outbound references

Observation 932c00b0-18dd-4e88-9c09-d2385501d9fd · outbound

This paper cites Longformer: The Long-Document Transformer.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention Longformer: The Long-Document Transformer

Reference 1

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source=pdf_text observed=2026-08-04T09:20:06.007749Z digest=sha256:9abad6c30a61f3a7e19f6d451a205e6533e82250a59f8ed685209ad7453638c8

Observation 9b18dbe6-2c68-4586-ba19-f00166c990ec · outbound

This paper cites HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer

Reference 4

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source=pdf_text observed=2026-08-04T09:20:06.234576Z digest=sha256:1ec9ab944e9cf71a6b8f249e6b064f973d7d7b32bda1eaf6f0fe9eaf0070a49e

Observation ef53952c-9f71-4539-a38c-60627b0dc3be · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 5

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source=pdf_text observed=2026-08-04T09:20:06.351589Z digest=sha256:a22e6a3d49088cc5b390e188c5dec722f9218c8d0257acf7dfd5189c89a4f4c0

Observation 041c5d06-2132-4dee-89d7-aaed139c5a31 · outbound

This paper cites FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference

Reference 8

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source=pdf_text observed=2026-08-04T09:20:06.613749Z digest=sha256:d74b561d8ba454f5765130ac431617912e263c0fbab63e126ff940c11bb77c08

Observation 870eade0-3460-4988-ad84-234f02bdce3b · outbound

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

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation

Reference 9

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source=pdf_text observed=2026-08-04T09:20:06.722617Z digest=sha256:73f098475a7e8f3f7a15bb8edfda11db82b42320ef2af51b9a6da3221d0bef35

Observation 144b3453-136f-451b-bc1d-609bdf09ad68 · outbound

This paper cites PolaFormer: Polarity-aware Linear Attention for Vision Transformers.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention PolaFormer: Polarity-aware Linear Attention for Vision Transformers

Reference 11

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source=pdf_text observed=2026-08-04T09:20:07.041132Z digest=sha256:5afc2ce0e6d6e7ff47714aac11cc911b0f5fa8fd4c43a4e9a002858869923de2

Observation 2c8f7331-3c53-46e0-bd94-e1ad0565aa00 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 12

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source=pdf_text observed=2026-08-04T09:20:07.195558Z digest=sha256:74d834d208d7af263b9e8acfc8fdc33250cef568ea3aef575932451a233e12c2

Observation 84494b1a-9ecc-4a22-bf2f-e3fc63f7f581 · outbound

This paper cites FreeScale: Unleashing the Resolution of Diffusion Models via Tuning-Free Scale Fusion.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention FreeScale: Unleashing the Resolution of Diffusion Models via Tuning-Free Scale Fusion

Reference 13

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source=pdf_text observed=2026-08-04T09:20:07.251023Z digest=sha256:431f3b2282a73856afd2789e1bb8bcfae9ad68556d8366a1668a6653caa6ec8a

Observation fc7f59fe-43c7-43d8-aebd-faa67ca10143 · outbound

This paper cites Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity

Reference 15

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source=pdf_text observed=2026-08-04T09:20:07.411349Z digest=sha256:eb9009805d970c4a06f6816b5df67f12f3a03fe2c350a673ec7a4ae53224de33

Observation 0a15cec0-087f-4439-bbab-1943028ed0fc · outbound

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

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

Reference 16

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source=pdf_text observed=2026-08-04T09:20:07.526556Z digest=sha256:0f1d1ceb20e94543c671c381a1d2974b08b4bc85b4d6278f14b8da18a5889082

Observation 5bd030a1-7d24-415d-9aa4-259401d341ae · outbound

This paper cites XAttention: Block Sparse Attention with Antidiagonal Scoring.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention XAttention: Block Sparse Attention with Antidiagonal Scoring

Reference 17

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source=pdf_text observed=2026-08-04T09:20:07.600476Z digest=sha256:1dd903b75752bca14b48f42baf1721b90facad08c4051047fdc6e3ffa5ac13f0

Observation a98bc80e-4815-4f0c-8dd3-b515437ca70b · outbound

This paper cites Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation

Reference 18

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source=pdf_text observed=2026-08-04T09:20:07.773723Z digest=sha256:c374c20776bb31a9f652ccb6815709db64fa8f6b4d63d2efe85328b8fd66b789

Observation e136a488-71f9-46b5-b5fc-95dfc93455f4 · outbound

This paper cites Ultra-Resolution Adaptation with Ease.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention Ultra-Resolution Adaptation with Ease

Reference 19

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source=pdf_text observed=2026-08-04T09:20:07.888542Z digest=sha256:168f307d1396569df2b48c027cfa70a3db76a088e0c2759e71553772b96d21da

Observation 42feef2d-24e6-4fe5-83cb-7bd4c4fe05be · outbound

This paper cites DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers

Reference 20

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source=pdf_text observed=2026-08-04T09:20:07.977364Z digest=sha256:0d777fb174aa436bc187a44c12470adc62056615dcd713720d52ffa2b55549cc

Observation bfb91ebf-b9f2-4f2c-9600-40707c4d24fe · outbound

This paper cites The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry

Reference 21

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source=pdf_text observed=2026-08-04T09:20:08.097591Z digest=sha256:1f7993d9169cce3c604d54758bcf3711b18c84238e3d5ad328260b0d715dd2d7

Observation 5a9ca147-f3bf-4c0e-ae26-bf3b043c1942 · outbound

This paper cites Our method is in leading position across all metrics.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention Our method is in leading position across all metrics

Reference 22

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source=pdf_text observed=2026-08-04T09:20:08.241880Z digest=sha256:21a0c8cb40d21bae93edfc7ebcde18e2996245d8ee24992eeac4980474724541

Observation 3f227d34-0c3d-4255-a5bb-4cb432dc0a98 · outbound

This paper cites FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space

Reference 2020

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source=pdf_text observed=2026-08-04T09:20:06.061301Z digest=sha256:1af80f9b2dd6f215afb5acdb46a18835f4bc7cf73da4947a1f3550017b79e882

Observation 5fe55a0e-1aaa-4385-a23c-50df94524068 · outbound

This paper cites Seedream 3.0 Technical Report.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention Seedream 3.0 Technical Report

Reference 2021

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source=pdf_text observed=2026-08-04T09:20:06.525522Z digest=sha256:d7b4a2f581f4a80d379c266d2208eba5a27a7169cb9461ce0300ef7c8c993054

Observation 6bbafdf3-6dff-4da1-ac68-89a60b371c21 · outbound

This paper cites LinFusion: 1 GPU, 1 Minute, 16K Image.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention LinFusion: 1 GPU, 1 Minute, 16K Image

Reference 2022

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source=pdf_text observed=2026-08-04T09:20:06.875247Z digest=sha256:42363a6bd1f6c7b19df9e0f94a488adf2d3952fbf666987c64f455a5a7870aba

Observation b9524794-c284-4117-ab34-f0b0ba46ae24 · outbound

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

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention PIXART-{\delta}: Fast and Controllable Image Generation with Latent Consistency Models

Reference 2023

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source=pdf_text observed=2026-08-04T09:20:06.446325Z digest=sha256:4c3d7da724109ee4845a3abd1149f29c7475bf1572d885b49c1be2a6726a6800

Observation d763430c-71b2-4c20-8c06-732094edf097 · outbound

This paper cites Relay Diffusion: Unifying diffusion process across resolutions for image synthesis.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention Relay Diffusion: Unifying diffusion process across resolutions for image synthesis

Reference 2024

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source=pdf_text observed=2026-08-04T09:20:07.298311Z digest=sha256:4f90a701d10229ec47ff8f75e82597f44542f9767238171ebeb920cc43109bf1

Observation 5a2785cf-b1a2-4737-b366-57c15ce2e4ca · outbound

This paper cites HiFlow: Training-free High-Resolution Image Generation with Flow-Aligned Guidance.

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention HiFlow: Training-free High-Resolution Image Generation with Flow-Aligned Guidance

Reference 2025

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source=pdf_text observed=2026-08-04T09:20:06.151128Z digest=sha256:042fd3f170f037598e238eb63d504dcb1c4573bbdae701e2b1d9c40310705f93

Pith citing papers

Observation 648cb113-d744-48ea-a9e0-9559df6ccef5 · inbound

HierEdit: Region-Aware Hierarchical Diffusion for Efficient High-Resolution Editing cites this paper.

HierEdit: Region-Aware Hierarchical Diffusion for Efficient High-Resolution Editing UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention

Reference 76

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arxiv_id, observed 2026-06-30T02:16:10.668452Z

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=2026-05-20T14:40:20.517450Z digest=sha256:f0855fdc30cefa2cb8b3f3643fa4a9f2e9e5d795b20c214faa12377e5a831215