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Paper Citation Record · LEDGER

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

As of 9 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 9 inbound Pith citation observations for arXiv:2502.06155.

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

pith.paper-citation-record.v1
2502.06155 v2

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:36:00.861663Z

measured 74 of 74 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:15:14.861189Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T18:14:17.525731Z

Reference resolution

65 of 65 outbound references displayed

  • verified exact2
  • verified fuzzy18
  • unresolved45
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 879f14bd-8897-4969-9900-68ec4584cc42 · outbound

This paper cites write newline.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.534034Z digest=sha256:e545831d890264cdfce435006dd4bf86516445664a03ce77b5f706fc57dcb850

Observation e2c047e6-018d-4017-9d2d-0c0849c635c9 · outbound

This paper cites Y., Suk, H., Suo, M., Tillet, P., Wang, E., Wang, X., Wen, W., Zhang, S., Zhao, X., Zhou, K., Zou, R., Mathews, A., Chanan, G., Wu, P., and Chintala, S.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Y., Suk, H., Suo, M., Tillet, P., Wang, E., Wang, X., Wen, W., Zhang, S., Zhao, X., Zhou, K., Zou, R., Mathews, A., Chanan, G., Wu, P., and Chintala, S

Reference 2

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source=arxiv_source observed=2026-08-08T16:36:00.541123Z digest=sha256:ec16aa858d05fc8cbc787272cbabfac96c1af48376731226ce0ee60ab4e40e6b

Observation 94fdb3b5-3a01-4cb0-b2ab-da78858b4676 · outbound

This paper cites Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion

Reference 3

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Observation 23dd000f-b5b3-4022-97f3-7505abd9fa95 · outbound

This paper cites Videocrafter2: Overcoming data limitations for high-quality video diffusion models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Videocrafter2: Overcoming data limitations for high-quality video diffusion models

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.975333Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.552831Z digest=sha256:7d1e768de2446e34d7ad70c2fcc020d67f045cc12508fbf236fde1033ac5c2fb

Observation 3617f228-9ea2-488b-ac75-bc512ca23935 · outbound

This paper cites Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers

Reference 5

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source=arxiv_source observed=2026-08-08T16:36:00.558029Z digest=sha256:021eba68f0036ab48839999a54c76c5ce4755b1dbd59506a1cc5699cd0e683ad

Observation 975d6dc2-04b2-4da4-9c6d-61c4045da716 · outbound

This paper cites AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising

Reference 6

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source=arxiv_source observed=2026-08-08T16:36:00.563170Z digest=sha256:4c41485bf98f0b9b7ede26016156b1a7351b28f487870a13cd7e827800f6a234

Observation f5d93968-c1ec-47fd-8386-7c3093811bdb · outbound

This paper cites Structure and content-guided video synthesis with diffusion models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Structure and content-guided video synthesis with diffusion models

Reference 7

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raw_fallback, observed 2026-08-08T16:36:01.959428Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.568777Z digest=sha256:5abc58219cd11156c5163f80e107ce042192c5640d0757ba9b764b374404669b

Observation f5140fd8-15b7-40e8-845d-d72673f0fbf0 · outbound

This paper cites Preserve your own correlation: A noise prior for video diffusion models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Preserve your own correlation: A noise prior for video diffusion models

Reference 8

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raw_fallback, observed 2026-08-08T16:36:01.943274Z

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

source=arxiv_source observed=2026-08-08T16:36:00.574079Z digest=sha256:ced98c73f3a3efc7a691453d44719ae4e0fa276991678aea137c5a1caa7caaed

Observation 6c56835c-c689-4e44-9464-c3a5b6ad6d80 · outbound

This paper cites Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs

Reference 9

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source=arxiv_source observed=2026-08-08T16:36:00.578900Z digest=sha256:ee527990495024d9aaf0dc56cb0b49e354402d3a9acbefdbade756d5e86306d4

Observation 95b604a4-94a5-46ee-a241-27d48f4770f4 · outbound

This paper cites On the Content Bias in Fr\'echet Video Distance.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile On the Content Bias in Fr\'echet Video Distance

Reference 10

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local_arxiv, observed 2026-08-08T16:36:01.413556Z

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

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Observation b06056eb-23ec-4515-9315-e6d092b44994 · outbound

This paper cites Minillm: Knowledge distillation of large language models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Minillm: Knowledge distillation of large language models

Reference 11

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source=arxiv_source observed=2026-08-08T16:36:00.593452Z digest=sha256:9f64dad38c582e650538a1c9f8ff4989a8479d23e5f69952cbfc8ad88db3ab0b

Observation 79bb3bb3-11da-4713-b672-1b9069214617 · outbound

This paper cites SparseCtrl: Adding Sparse Controls to Text-to-Video Diffusion Models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile SparseCtrl: Adding Sparse Controls to Text-to-Video Diffusion Models

Reference 12

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source=arxiv_source observed=2026-08-08T16:36:00.598080Z digest=sha256:47bd6e12f8b405936285d9260054beb0fdc89c0d4db27cf01f34754829bc859d

Observation 2b792012-9c03-4fad-a65b-fc3bd61c0616 · outbound

This paper cites Animatediff: Animate your personalized text-to-image diffusion models without specific tuning.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Animatediff: Animate your personalized text-to-image diffusion models without specific tuning

Reference 13

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source=arxiv_source observed=2026-08-08T16:36:00.603175Z digest=sha256:94ff73532ce75b1768a22774432073b6205ea35b0fc281962fb9bdda53d59f0e

Observation d397fb01-a86c-4445-9c71-b94dde4ecc35 · outbound

This paper cites Latent Video Diffusion Models for High-Fidelity Long Video Generation.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Latent Video Diffusion Models for High-Fidelity Long Video Generation

Reference 14

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source=arxiv_source observed=2026-08-08T16:36:00.608167Z digest=sha256:02bf9a0ee1910690d313daef4a05ead8a8a19f6bb716770a006cf0182856be23

Observation 81427793-320b-4014-a568-6d264499d586 · outbound

This paper cites Multistep Consistency Models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Multistep Consistency Models

Reference 15

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source=arxiv_source observed=2026-08-08T16:36:00.613132Z digest=sha256:8b48c89a33101ca741582737141b553a0f24444bcd5b68d1ac883a8e093db49f

Observation d574554b-c171-469c-8e83-d1eb0ff321a1 · outbound

This paper cites StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text

Reference 16

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source=arxiv_source observed=2026-08-08T16:36:00.618081Z digest=sha256:86b559a6d0081c92c97ff6cb05234df0162e3853a30dffcb6d0379353b82a2eb

Observation 8c2a1d30-9d77-4ce8-8a82-d5055a71632b · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Distilling the Knowledge in a Neural Network

Reference 17

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source=arxiv_source observed=2026-08-08T16:36:00.623076Z digest=sha256:d73aa10175bf2d5848ff2231599f51c8f4c655762d58344513eadb569ce0b108

Observation 4128552a-5a2b-480d-9054-de6b48d2bd65 · outbound

This paper cites an unresolved cited work.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Unresolved cited work

Reference 18

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source=arxiv_source observed=2026-08-08T16:36:00.628369Z digest=sha256:70065f7ed2096a1673be6d2700f155682d102fa7defa277098c0d63ef4270070

Observation 08444821-546c-4338-8499-1097e243eb58 · outbound

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

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Vbench: Comprehensive benchmark suite for video generative models

Reference 19

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source=arxiv_source observed=2026-08-08T16:36:00.633493Z digest=sha256:446753dbbf68327f4175878698dc8209dd0c5b091e71cb60c7ca51bf9ce4eac5

Observation 8c3f9113-e61b-4bff-a736-3c791cd2e5bd · outbound

This paper cites DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models

Reference 20

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source=arxiv_source observed=2026-08-08T16:36:00.638410Z digest=sha256:f291e3421d8efdf2b62a9d7235f39af0292a6935b5327889ee01f10bb67cf80a

Observation 373c26d2-28b7-4781-a4cf-40710192aefa · outbound

This paper cites TinyBERT: Distilling BERT for Natural Language Understanding.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile TinyBERT: Distilling BERT for Natural Language Understanding

Reference 21

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source=arxiv_source observed=2026-08-08T16:36:00.644229Z digest=sha256:a0cc4a8eea240eba9c670d7176c0703eec91d099e12acfb346932b00be5316e2

Observation ee4c3a19-5c23-4914-89ff-83d79a0ea2e2 · outbound

This paper cites Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion

Reference 22

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source=arxiv_source observed=2026-08-08T16:36:00.649412Z digest=sha256:6380065d7df50b36a96751a95b4d0f3dc87aa0a78c609359f52d5dcfe5787623

Observation 52f6ec41-0aa7-48ea-919c-40820754231b · outbound

This paper cites Kling, 2024.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Kling, 2024

Reference 23

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raw_fallback, observed 2026-08-08T16:36:01.881048Z

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

source=arxiv_source observed=2026-08-08T16:36:00.654609Z digest=sha256:1e57b37129b4d690088ee5e6658e626ff109649e98abb760ee1b54ccfc47f216

Observation ec3a272e-1247-4ef0-a729-a882cd471b99 · outbound

This paper cites and etc., T.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile and etc., T

Reference 24

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source=arxiv_source observed=2026-08-08T16:36:00.659388Z digest=sha256:c8805688c331c29869241a4e4e67432185a78a6b0cb1bba5cca18a681794e75a

Observation ba841194-aa46-4883-be2b-dbf16191b945 · outbound

This paper cites P., Ma, X., Stoica, I., Gonzalez, J.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile P., Ma, X., Stoica, I., Gonzalez, J

Reference 25

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raw_fallback, observed 2026-08-08T16:36:01.865018Z

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

source=arxiv_source observed=2026-08-08T16:36:00.664372Z digest=sha256:e4ca16166d35dd8d1b15a15a03dfd4d2969ec75523593539124867376c56f304

Observation f1194f38-bc35-473c-bff2-3b3ba0fd07fa · outbound

This paper cites T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 26

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source=arxiv_source observed=2026-08-08T16:36:00.669349Z digest=sha256:9590e46d95f2fa3eebed4f8c5d371df4839428e9c0d4eb8cf7af255868be5298

Observation 1ea50d30-0989-4e70-9fea-4c677e1b1951 · outbound

This paper cites Gan compression: Efficient architectures for interactive conditional gans.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Gan compression: Efficient architectures for interactive conditional gans

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.848657Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.675076Z digest=sha256:cdf070fce42d8e87aec07ef9c5392773c5b304248aaec62c316e167aab6132a2

Observation 6117cdd6-ea7e-47c8-9858-4876a5d0c5f0 · outbound

This paper cites Efficient spatially sparse inference for conditional gans and diffusion models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Efficient spatially sparse inference for conditional gans and diffusion models

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.832465Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.680165Z digest=sha256:0473d964991ac4b2a45643b7c6ac0a2301a533d69a445f2ff5306115e68b808c

Observation 9e7e5081-aa54-4346-88b7-55968b2cb0ae · outbound

This paper cites Distrifusion: Distributed parallel inference for high-resolution diffusion models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Distrifusion: Distributed parallel inference for high-resolution diffusion models

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.815764Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.684959Z digest=sha256:110560e86681ac08f8d5d5cf13d20b7cefd37217f8c119969c43a8a7a926dca8

Observation 8a6531b9-4286-46d4-b2f5-4ba4884aa181 · outbound

This paper cites Ring Attention with Blockwise Transformers for Near-Infinite Context.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Ring Attention with Blockwise Transformers for Near-Infinite Context

Reference 30

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source=arxiv_source observed=2026-08-08T16:36:00.689851Z digest=sha256:63215e34102ed800ff1b1a808fd77e18e11274058e8ef86e5e97f59c6d9e0b12

Observation 34ff312d-c82d-4f7b-8a16-a27331ac2984 · outbound

This paper cites SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation

Reference 31

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source=arxiv_source observed=2026-08-08T16:36:00.694874Z digest=sha256:7a6f425509f4808363137aee5f2abdcc22e565a0dc1044c0626db82268b96e5d

Observation 6395adc7-bdb8-4d45-8888-63c79c31f51c · outbound

This paper cites Instaflow: One step is enough for high-quality diffusion-based text-to-image generation.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Instaflow: One step is enough for high-quality diffusion-based text-to-image generation

Reference 32

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source=arxiv_source observed=2026-08-08T16:36:00.699889Z digest=sha256:163310957d9613697980e94df486244d6ad05b36f61fa627c7621977070ff68b

Observation 210e0a49-8d13-4b2f-8a6a-fc9b75f451a7 · outbound

This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.790332Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.704323Z digest=sha256:95dc10d4097768186ab76067e7d65450c04682ecdebdf291c284bd85f6142aaf

Observation c48b333d-5f01-4c90-8b43-5a44db7eee13 · outbound

This paper cites DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

Reference 34

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source=arxiv_source observed=2026-08-08T16:36:00.709202Z digest=sha256:7879eb71147c5fa0e55b1e9d154754499c53e1ffeec8b84872bb6233ccefd568

Observation 09ebc99d-2e30-493a-99e6-02c869278f38 · outbound

This paper cites Videofusion: Decomposed diffusion models for high-quality video generation.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Videofusion: Decomposed diffusion models for high-quality video generation

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.774778Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.714008Z digest=sha256:09c441b7cc764a4556a2680ac34bf1224458c4a43f0e716cc40bf63dcfd68c0b

Observation 4369801d-eae4-41d2-9d92-d0386cb75f01 · outbound

This paper cites Latte: Latent Diffusion Transformer for Video Generation.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Latte: Latent Diffusion Transformer for Video Generation

Reference 36

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.718429Z digest=sha256:deb014bec791e082db27600f988d1b0ba7717c09874c144c06dd806e291bf702

Observation df435bc0-cfe3-44b0-aeff-f205b4536f37 · outbound

This paper cites and Lee, W.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile and Lee, W

Reference 37

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source=arxiv_source observed=2026-08-08T16:36:00.723424Z digest=sha256:6eee010748e308b6aa8af61f304807aa19d57fa6b122371af79c1c76c0555bdb

Observation cca92412-a4ac-4814-9aee-d89e3f6c4bf8 · outbound

This paper cites Sora, 2024.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Sora, 2024

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.759391Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.728113Z digest=sha256:455ddca39c4b1d189fb1409caa97f94b4d3442cca35ce1d100830c6197014c09

Observation 71f51c61-a5a8-47b6-b1c6-029caaba7697 · outbound

This paper cites and Xie, S.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile and Xie, S

Reference 39

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source=arxiv_source observed=2026-08-08T16:36:00.733125Z digest=sha256:b397f3c63c6e9e2f17ff53d2bb06286ce5bcd1744480195215c293f6be039378

Observation f95b307f-42c2-4129-a6fd-3bf2ab82a32d · outbound

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

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile High-resolution image synthesis with latent diffusion models

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.734673Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.737723Z digest=sha256:b12d4e1599d31598b35b3ba8e6bdb418c0f01af8749abc64465a2b78d843b288

Observation d9a83c0a-1467-4d86-853a-eb68bd8eaeee · outbound

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

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile High-resolution image synthesis with latent diffusion models

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.718989Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.742357Z digest=sha256:b8973aff9fbb6dfc56d590c189ee68ef907a76d5ac75d3efa8a288098590b8e2

Observation c68dbbd0-a155-4ac4-8e39-e520e894b14f · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Progressive Distillation for Fast Sampling of Diffusion Models

Reference 42

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.747307Z digest=sha256:2124ee5d502912e765870b676020284c05b6eb92fe2662eaf9cc02ddb67975ac

Observation ae08ac42-847a-4636-ab6c-70423dbdd4a0 · outbound

This paper cites Adversarial Diffusion Distillation.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Adversarial Diffusion Distillation

Reference 43

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.753095Z digest=sha256:0e5db9630b15a28d64f40861ad081e6a3f0b7a548af6443ec0c9fb0c9ecf3698

Observation d3c89bfd-6543-412a-ac7b-0ced928d0023 · outbound

This paper cites Denoising Diffusion Implicit Models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Denoising Diffusion Implicit Models

Reference 44

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.758040Z digest=sha256:71dc19b9c9a1c282c6e945f56191d68fbc5e60b0f4a12cf57c3aeeda61432996

Observation 75110f21-8cc3-4805-8c5d-3b1bdc07800e · outbound

This paper cites Consistency Models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Consistency Models

Reference 45

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.763069Z digest=sha256:15899ed3d9210dcd7aeb034564f286f95e89195423f21066c7fa35b7a612f410

Observation a543757e-31a1-43ac-90c6-f7400c65e591 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Roformer: Enhanced transformer with rotary position embedding

Reference 46

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no resolver link, observed 2026-08-08T16:36:00.767848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.767848Z digest=sha256:6a23cb2c5d7e7da8f7076ae9362ebba0583c07f9532a358f4eeedd0c51e63f3c

Observation b7a74510-49f8-4de6-a7b3-1a8765b6c936 · outbound

This paper cites Diffusion Models Are Real-Time Game Engines.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Diffusion Models Are Real-Time Game Engines

Reference 47

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no resolver link, observed 2026-08-08T16:36:00.772590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.772590Z digest=sha256:c2d7b9ab25f6656ec333f64017c93b4b383391f3c58f36c3d7b3a19059088da1

Observation 962af9a9-3917-4d53-8bb3-db2c8ba70ff0 · outbound

This paper cites Cuttlefish: Low-rank model training without all the tuning.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Cuttlefish: Low-rank model training without all the tuning

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.693012Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.777502Z digest=sha256:bc62f56d3ba8533347e01f02b8b446bd0e3fec1e0346dad9541f3777b34ffea2

Observation 69b1b477-c1dd-4da0-b5e0-3b25019a5d32 · outbound

This paper cites PipeFusion: Patch-level Pipeline Parallelism for Diffusion Transformers Inference.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile PipeFusion: Patch-level Pipeline Parallelism for Diffusion Transformers Inference

Reference 49

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.782163Z digest=sha256:ed923721d4a3b6b7f26eaedd2ce57671a1041bdc8ac5ca9dbdf34aa81c8d1d33

Observation 0fb27e87-ed33-484a-86bd-24e83633a040 · outbound

This paper cites Qihoo-T2X: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Any-Task.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Qihoo-T2X: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Any-Task

Reference 50

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verified exact
local_arxiv, observed 2026-08-08T16:36:01.090091Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.787293Z digest=sha256:7a1f3d3d151356876b6ab2d70e94343849610381ba64f45ce4ffd84c9e3a2d28

Observation 586ff3f7-6c6c-4c4a-8596-c622ab16b7c8 · outbound

This paper cites VideoLCM: Video Latent Consistency Model.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile VideoLCM: Video Latent Consistency Model

Reference 51

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no resolver link, observed 2026-08-08T16:36:00.792125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.792125Z digest=sha256:e2eb2a2cda04a67ff58c0ebc6ede8a5a767409ef6cf716f5ed12a84c57859e8d

Observation 505231f3-b775-4e20-8697-4982d873e473 · outbound

This paper cites LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

Reference 52

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no resolver link, observed 2026-08-08T16:36:00.797146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.797146Z digest=sha256:64d71002ed5453fb1d3e698314d06a3c0d0f3fa433ca4395acb49556e416c5bf

Observation 5f3bfb9b-99d0-41a7-87be-8553a1dfd701 · outbound

This paper cites Pandora: Towards General World Model with Natural Language Actions and Video States.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Pandora: Towards General World Model with Natural Language Actions and Video States

Reference 53

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no resolver link, observed 2026-08-08T16:36:00.802081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.802081Z digest=sha256:f553a6694dc1af173aabae442133990a0ffe37200710fb059540b6ab9762e91f

Observation 045bff2a-e539-43cd-80cd-901e0b89437b · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Efficient Streaming Language Models with Attention Sinks

Reference 54

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no resolver link, observed 2026-08-08T16:36:00.806932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.806932Z digest=sha256:fa0ac27936cee40d7defa576e3a8c4f57aba364f6e89824351e3dc1cbb64d567

Observation 9de7b43a-c1d2-4d43-8971-9a792400f717 · outbound

This paper cites TLCM: Training-efficient Latent Consistency Model for Image Generation with 2-8 Steps.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile TLCM: Training-efficient Latent Consistency Model for Image Generation with 2-8 Steps

Reference 55

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no resolver link, observed 2026-08-08T16:36:00.811851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.811851Z digest=sha256:1aa705b013ca0c0760449e79975d7ef44662e770934f4a8a1f7e9307e1e6b920

Observation d942cf6c-18c6-4c23-948e-73da7d12d445 · outbound

This paper cites LongVILA: Scaling Long-Context Visual Language Models for Long Videos.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Reference 56

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no resolver link, observed 2026-08-08T16:36:00.816958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.816958Z digest=sha256:5aaca4142c05d5136f9599dad0f0c014c0bc9def823093ed3047cfd37df63ee6

Observation da45e496-bf4d-48ae-91b9-c1f1b5849839 · outbound

This paper cites mT5: A massively multilingual pre-trained text-to-text transformer.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile mT5: A massively multilingual pre-trained text-to-text transformer

Reference 57

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no resolver link, observed 2026-08-08T16:36:00.821782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.821782Z digest=sha256:d81f6ae59b9ec2af14223993f507d13460b069b4db694debde7251d3fad999b3

Observation 2239970b-c879-4ee0-a22c-4c9f7a1fa120 · outbound

This paper cites PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference

Reference 58

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no resolver link, observed 2026-08-08T16:36:00.827553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.827553Z digest=sha256:6518e1653bbf253dd67cd8ae7780a27f3941a5190d5eb4b28298982b299d5916

Observation 7a8a4519-ee6a-4f1e-8643-46e7dffecd73 · outbound

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

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 59

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no resolver link, observed 2026-08-08T16:36:00.832860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.832860Z digest=sha256:aa392b9f692916776a2767362d7c7f232dccce599a91da92e9ee5b848573fc4b

Observation 39034598-b7e8-44b1-a69c-6b5c30bdb504 · outbound

This paper cites T., and Park, T.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile T., and Park, T

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.676982Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.837623Z digest=sha256:e2c05bc33e3bee54287dbb6525cc3a714da4b023a75b3504d0d22e2fe9141741

Observation 8725a39c-57b3-4256-a970-bc42a964c472 · outbound

This paper cites S., Kim, G.-W., Kim, S., and Chun, B.-G.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile S., Kim, G.-W., Kim, S., and Chun, B.-G

Reference 61

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unresolved
no resolver link, observed 2026-08-08T16:36:00.842255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.842255Z digest=sha256:4687bd7df03306b5337c72d37a52d902ff7770e9c8a7b62be2502a7d34202d86

Observation 3ae35f44-79de-4022-a59b-27ccad8757b2 · outbound

This paper cites Q-hitter: A better token oracle for efficient llm inference via sparse-quantized kv cache.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Q-hitter: A better token oracle for efficient llm inference via sparse-quantized kv cache

Reference 62

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.649692Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.846932Z digest=sha256:12ee01d09f4102fbd8fff2ff1fd375f7440d9d8f256cc22a13e6ab9ef58f1366

Observation f39a16b3-dd90-4c9b-967d-e44aa98714ae · outbound

This paper cites H2o: Heavy-hitter oracle for efficient generative inference of large language models.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile H2o: Heavy-hitter oracle for efficient generative inference of large language models

Reference 63

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.634544Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.851818Z digest=sha256:00668fb1132031b889fcaa9bf367bcf0881862e929fe8c2535f7aeea94173461

Observation 66cc62c7-cdbc-4ebc-a43a-82c162f99ce3 · outbound

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

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Real-Time Video Generation with Pyramid Attention Broadcast

Reference 64

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no resolver link, observed 2026-08-08T16:36:00.856578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:36:00.856578Z digest=sha256:e3e4454f915f81d39e0af12a30c76db38fd4859c2799a82f65cc80230ea7cb10

Observation 02022250-effe-41ba-b5b2-f5ebfd8b6a11 · outbound

This paper cites Open-sora: Democratizing efficient video production for all, March 2024.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Open-sora: Democratizing efficient video production for all, March 2024

Reference 65

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verified fuzzy
raw_fallback, observed 2026-08-08T16:36:01.618102Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-08T16:36:00.861663Z digest=sha256:821b37f62214a0b5bad18a296afb7971b8dee27a06b29b2c6c0ab94ba81b3833

Pith citing papers

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

Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers cites this paper.

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

Reference 6

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:15:14.861189Z digest=sha256:42626f5c32b19ff47d37ad1444832c84b447c14650261e8220fc8749d6e25b56

Observation 16db170a-0ee8-4b88-b45f-2067dfdae9be · inbound

Timeripple: Accelerating vDiTs by Understanding the Spatio-Temporal Correlations in Latent Space cites this paper.

Timeripple: Accelerating vDiTs by Understanding the Spatio-Temporal Correlations in Latent Space Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

Reference 8

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unresolved
no resolver link, observed 2026-08-03T22:12:43.020208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:12:43.020208Z digest=sha256:25b74efa22af2fa9b08420fdc2c123e69eeb36d378574431f7bf4a6a4b466c0c

Observation 973b95b9-d8d5-4b68-b726-7c95623b619c · inbound

FrameDiT: Diffusion Transformer with Matrix Attention for Efficient Video Generation cites this paper.

FrameDiT: Diffusion Transformer with Matrix Attention for Efficient Video Generation Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-15T13:30:01.676254Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-15T13:27:23.641294Z digest=sha256:ec4328eb72984611a7068d59e2d6bfec4684d60c1e4b0a9c0293c42f991d86d0

Observation 1cd29495-3fdc-4fb0-b51f-6c0b3c14d5f8 · inbound

SURF: Signature-Retained Fast Video Generation cites this paper.

SURF: Signature-Retained Fast Video Generation Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-21T18:14:17.530161Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-21T18:11:39.642701Z digest=sha256:29812c83b57bc24e1a4155b281602a8e267226bf7372a3eca90e591762b3a969

Observation 2045bde9-21ee-41bd-a5a1-7b8dcb8be5b8 · inbound

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

Efficient Video Diffusion Models: Advancements and Challenges Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

Reference 253

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:03:26.274718Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-10T08:28:29.706249Z digest=sha256:60b460429d13233e5dd46e8b5d042af58baf33f6bacb6742fb6255eebcc17287

Observation 3a8ccec0-e467-4c0b-975b-0a4a56fcb7f0 · inbound

Kaleido: Algorithm-Hardware Co-Design for Video Diffusion Transformers by Exploiting Latent Space Correlations cites this paper.

Kaleido: Algorithm-Hardware Co-Design for Video Diffusion Transformers by Exploiting Latent Space Correlations Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

Reference 12

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no resolver link, observed 2026-08-02T03:51:43.943264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T03:51:43.943264Z digest=sha256:daab746c51ad54c52440706e7e8208478b79b87a67e83da8d1f9430e11c0dea0

Observation d95da06c-d323-4e3b-8906-bdae06a2850c · inbound

CODA: Algorithm-Hardware Co-design for Edge Video Diffusion via NMP-Enabled Compute-Cache Operator Disaggregation cites this paper.

CODA: Algorithm-Hardware Co-design for Edge Video Diffusion via NMP-Enabled Compute-Cache Operator Disaggregation Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-02T00:49:33.632515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T00:49:33.632515Z digest=sha256:59362da82bd4c83240b152658583279e764832b7691d554300966e1d96400fea

Observation 2ed05fa7-6588-4b8f-a38b-f139a7e59178 · inbound

Chimera: Designing and Chinchilla-Scaling Hybrid Visual Diffusion Transformers cites this paper.

Chimera: Designing and Chinchilla-Scaling Hybrid Visual Diffusion Transformers Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-31T02:16:07.984738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:16:07.984738Z digest=sha256:3d9f2423e90e120139e3f805d773bfb38db78e8589079b364c3b05f901621f83

Observation 2130302b-c659-4d29-bfc2-118e11d201be · 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 Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T20:50:03.963203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:50:03.963203Z digest=sha256:b5e76b8da23d1db487910e7bd30b4a9ed8dab9371e115f6df34e569b40c4687c