Paper Citation Record · LEDGER

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

As of 9 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 11 inbound Pith citation observations for arXiv:2506.03065.

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

pith.paper-citation-record.v1
2506.03065 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:15:18.581949Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:50:03.947151Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:49:44.825271Z

Reference resolution

51 of 51 outbound references displayed

verified exact0
verified fuzzy8
unresolved42
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation afe33d08-fe92-432b-ae1a-471921e8a8b4 · outbound

This paper cites Longformer: The Long-Document Transformer.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Longformer: The Long-Document Transformer

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:14.392823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11ee65f5-0dba-4961-9e6f-9d909588bd2a · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:14.494535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4292088d-975d-4d55-9069-e1445ce8c2d5 · outbound

This paper cites Ld-pruner: Ef- ficient pruning of latent diffusion models using task-agnostic insights.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Ld-pruner: Ef- ficient pruning of latent diffusion models using task-agnostic insights

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:14.604960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2827ffec-b6e0-424d-9e2f-d85e9e39bd39 · outbound

This paper cites $\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers $\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:14.714375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb21d783-e0b0-42f4-bf03-c471abc5243d · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Generating Long Sequences with Sparse Transformers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:14.783778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 008a59f2-17ab-48b3-91c7-ab475280a28d · outbound

This paper cites Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:14.861189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80444ff7-37e0-495c-8dc2-99dce13b4358 · outbound

This paper cites Scaling Rectified Flow Transformers for High-Resolution Image Synthesis.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:14.919834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57ae08fa-4ebf-4722-935b-c2d05eb92350 · outbound

This paper cites Structural pruning for diffusion models.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Structural pruning for diffusion models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:15:20.118445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 816893ad-16f6-4cfb-9959-e4b0df2676f7 · outbound

This paper cites Neighborhood attention transformer.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Neighborhood attention transformer

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:15.131954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ec664b1-d70f-464c-b996-844981a4de2a · outbound

This paper cites Pre-Trained Video Generative Models as World Simulators.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Pre-Trained Video Generative Models as World Simulators

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:15.192689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa396819-df35-4c58-9cf3-c4ebd7ea91d6 · outbound

This paper cites Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:15.291377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d05a333-f744-4c2a-b9d0-f5d926f63550 · outbound

This paper cites Animate anyone: Consistent and controllable image-to-video synthesis for character animation.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Animate anyone: Consistent and controllable image-to-video synthesis for character animation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:15:19.977505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 01a894a9-e7c8-42f0-a2dc-423e4c1a28aa · outbound

This paper cites Vbench: Comprehensive benchmark suite for video generative models.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Vbench: Comprehensive benchmark suite for video generative models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:15.493451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a30a21f-b308-4d8a-a49f-d2c786c475e7 · outbound

This paper cites Minference 1.0: Accelerating pre-filling for long-context llms via dynamic sparse attention.Advances in Neural Information Processing Systems, 37:52481–52515, 2024.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Minference 1.0: Accelerating pre-filling for long-context llms via dynamic sparse attention.Advances in Neural Information Processing Systems, 37:52481–52515, 2024

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:15.586946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82fa8275-d35d-4172-8333-c53ecb4f40be · outbound

This paper cites Adaptive Caching for Faster Video Generation with Diffusion Transformers.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Adaptive Caching for Faster Video Generation with Diffusion Transformers

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:15.704247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31a7549c-480a-45fa-9364-fa2da046fab1 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:15.801169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bfbc421-98c1-467d-a47e-8c7bdcfe314a · outbound

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

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:15.864790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9328eb4b-3f0a-4c56-bef5-d61349337019 · outbound

This paper cites Open-Sora Plan: Open-Source Large Video Generation Model.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Open-Sora Plan: Open-Source Large Video Generation Model

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:15.930372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55920021-a95f-42b0-80e6-661be7bc7920 · outbound

This paper cites Diffusion adversarial post-training for one-step video generation.arXiv preprint arXiv:2501.08316, 2025.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Diffusion adversarial post-training for one-step video generation.arXiv preprint arXiv:2501.08316, 2025

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.001509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecff04f6-bdca-4c98-b052-00923f6c1cef · outbound

This paper cites Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.056909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 819697d8-6b6f-453f-afef-8326d1911db9 · outbound

This paper cites CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.170658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4619a122-399c-4073-8e37-cd9583cd1fac · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Swin transformer: Hierarchical vision transformer using shifted windows

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.222163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b0d94a6-e522-45d3-b7c0-b8109eec9798 · outbound

This paper cites FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.311954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce59189e-b970-4f39-a222-fb9665cb49f9 · outbound

This paper cites Deepcache: Accelerating diffusion models for free.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Deepcache: Accelerating diffusion models for free

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.389068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec6d1b80-03d1-47a5-919d-6c805ff1082f · outbound

This paper cites Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.497799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 357eba18-fac0-4ec5-8fb1-aff71f81e27e · outbound

This paper cites Scalable diffusion models with transformers.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Scalable diffusion models with transformers

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.586188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a617c6d5-21a8-4ede-bfda-125ba76e3be3 · outbound

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

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers High- resolution image synthesis with latent diffusion models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.680560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d3c533e-c998-4540-ac8f-a6575e1435fc · outbound

This paper cites Post-training quantization on diffusion models.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Post-training quantization on diffusion models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:15:19.773754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 66961187-1e0a-4f09-9bc2-81c586e7b42e · outbound

This paper cites MD-dit: Step-aware mixture-of-depths for efficient diffusion transformers.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers MD-dit: Step-aware mixture-of-depths for efficient diffusion transformers

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:15:19.657568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a1d97e77-f827-405d-92dd-6aaf73342a61 · outbound

This paper cites REDUCIO! Generating 1K Video within 16 Seconds using Extremely Compressed Motion Latents.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers REDUCIO! Generating 1K Video within 16 Seconds using Extremely Compressed Motion Latents

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.889183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65cb2c5f-47ee-4a1e-954e-87c25a2dba23 · outbound

This paper cites Triton: an intermediate language and compiler for tiled neural network computations.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Triton: an intermediate language and compiler for tiled neural network computations

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:16.969476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b95db35-90b3-4bd5-8322-65f8cd92703d · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers LLaMA: Open and Efficient Foundation Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:17.100784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5f83350-da94-45a8-ae81-389529d36905 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:17.174838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9508745a-2707-407d-bf3c-c7cb80e309aa · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Wan: Open and Advanced Large-Scale Video Generative Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:17.312148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01a36b3c-7a2b-4268-b0cd-e644168d0c1a · outbound

This paper cites Taming Rectified Flow for Inversion and Editing.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Taming Rectified Flow for Inversion and Editing

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:17.421351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f901e63f-848b-410c-aa41-fcdc43698073 · outbound

This paper cites A universal image quality index.IEEE signal processing letters, 9(3):81–84, 2002.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers A universal image quality index.IEEE signal processing letters, 9(3):81–84, 2002

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:15:19.454645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 48ef1737-aea0-4d16-8b0f-7eff42736ed0 · outbound

This paper cites PTQ4DiT: Post-training Quantization for Diffusion Transformers.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers PTQ4DiT: Post-training Quantization for Diffusion Transformers

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:17.600341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7e096eb-6989-47c4-b97d-ae330f0af6cf · outbound

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

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:17.692975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a2310c5-0489-47ab-9507-9fb286ca6155 · outbound

This paper cites DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:17.818811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89422a6f-e3c9-4110-8a11-52789c4060a8 · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Efficient Streaming Language Models with Attention Sinks

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:17.899959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61c2594e-de15-4db9-9916-604867f466f5 · outbound

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

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:17.947369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8ee225c-35fb-4915-afcb-57e13eb2f44d · outbound

This paper cites Dynamicrafter: Animating open-domain images with video diffusion priors.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Dynamicrafter: Animating open-domain images with video diffusion priors

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:18.000721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b69334d9-a790-4463-ab78-c6d493652f41 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:18.074114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d5b2940-0fed-4dcc-b58a-aab97b4b341c · outbound

This paper cites Ditfastattn: Attention compression for diffusion transformer models.Advances in Neural Information Processing Systems, 37:1196–1219, 2024.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Ditfastattn: Attention compression for diffusion transformer models.Advances in Neural Information Processing Systems, 37:1196–1219, 2024

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:15:19.301120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 638d182d-b4c7-476b-88c6-873c9e37be02 · outbound

This paper cites Motion consistency model: Accelerating video diffusion with disentangled motion-appearance distillation.Advances in Neural Information Processing Systems, 37:111000–111021, 2024.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Motion consistency model: Accelerating video diffusion with disentangled motion-appearance distillation.Advances in Neural Information Processing Systems, 37:111000–111021, 2024

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:15:19.171343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5daa6921-079d-4f24-943a-1ee2dcc981b3 · outbound

This paper cites InstructVEdit: A Holistic Approach for Instructional Video Editing.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers InstructVEdit: A Holistic Approach for Instructional Video Editing

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:18.258170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55d919ff-f73d-4561-87b5-7e1836b9f89d · outbound

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

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:18.309915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c4bc236-ea8a-4fbf-8cc6-e223d5ca6900 · outbound

This paper cites The unrea- sonable effectiveness of deep features as a perceptual metric.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers The unrea- sonable effectiveness of deep features as a perceptual metric

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:18.375024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e98e2f2-69ff-4ace-a17c-31c298d5ede7 · outbound

This paper cites Pioneering 4-bit fp quantization for diffusion models: Mixup-sign quantization and timestep-aware fine-tuning, 2025.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Pioneering 4-bit fp quantization for diffusion models: Mixup-sign quantization and timestep-aware fine-tuning, 2025

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:15:19.024778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7785b33f-34ad-4b07-b343-b05afabecfbd · outbound

This paper cites Real-Time Video Generation with Pyramid Attention Broadcast.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers Real-Time Video Generation with Pyramid Attention Broadcast

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:18.510621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d3c4f4e-e987-4af4-a5db-a2c5a4471d8f · outbound

This paper cites DiG: Scalable and Efficient Diffusion Models with Gated Linear Attention.

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers DiG: Scalable and Efficient Diffusion Models with Gated Linear Attention

Reference 51

Resolution: malformed identifier; no resolver link, observed 2026-08-07T11:15:18.581949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 5588daa0-1b4c-4c7b-a408-50218720e742 · inbound

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer cites this paper.

Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T20:30:26.075671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67a6f03d-8ad4-450c-a056-0638d32f6739 · inbound

Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers cites this paper.

Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T15:35:13.213540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a628508-83c3-47b5-a8ac-a9d5b7d00b11 · inbound

Mixture of Distributions Matters: Dynamic Sparse Attention for Efficient Video Diffusion Transformers cites this paper.

Mixture of Distributions Matters: Dynamic Sparse Attention for Efficient Video Diffusion Transformers Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T10:37:47.271073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72a290b8-0d04-49ef-85a3-f30d74098ea3 · inbound

Ride the Wave: Precision-Allocated Sparse Attention for Smooth Video Generation cites this paper.

Ride the Wave: Precision-Allocated Sparse Attention for Smooth Video Generation Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:46:02.769647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fcf2776e-34b9-4b9b-96c2-553a28bf05a7 · inbound

Efficient Video Diffusion Models: Advancements and Challenges cites this paper.

Efficient Video Diffusion Models: Advancements and Challenges Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 238

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:03:25.984657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c509e37d-a7a3-44e1-bc6f-91d1390c36b5 · inbound

HASTE: Training-Free Video Diffusion Acceleration via Head-Wise Adaptive Sparse Attention cites this paper.

HASTE: Training-Free Video Diffusion Acceleration via Head-Wise Adaptive Sparse Attention Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:19:46.210669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1f7c32e5-9011-4239-949e-e4e86e825e2c · inbound

Veda: Scalable Video Diffusion via Distilled Sparse Attention cites this paper.

Veda: Scalable Video Diffusion via Distilled Sparse Attention Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:03:14.729248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 53268387-2a8c-422e-81a0-a77bba15a33d · inbound

PAI-Studio: Cinematic Video Background Replacement with Camera-Aware Motion cites this paper.

PAI-Studio: Cinematic Video Background Replacement with Camera-Aware Motion Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:16:14.715737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3cb0ef35-9ca6-45fa-9632-d9a643d66168 · inbound

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization cites this paper.

TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 70

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T00:56:24.913950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2250f170-1136-4b46-9d7c-fa8567d37eb4 · inbound

ScalingAttention: Discovering Intrinsic Sparse Attention Topology for Video Diffusion Transformers cites this paper.

ScalingAttention: Discovering Intrinsic Sparse Attention Topology for Video Diffusion Transformers Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T09:49:44.826596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5468d60f-563f-43f9-a3f7-aeeccec62463 · inbound

SPADE: An Input-Adaptive Sparse Attention Engine for Fast Video Diffusion Models Inference cites this paper.

SPADE: An Input-Adaptive Sparse Attention Engine for Fast Video Diffusion Models Inference Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T20:50:03.947151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.