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Paper Citation Record · LEDGER

DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2503.22796.

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

pith.paper-citation-record.v1
2503.22796 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:15:18.309915Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T19:43:54.712585Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

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

source=pdf_text observed=2026-08-07T11:15:18.309915Z digest=sha256:edbf481ed7cb781b5001e78fc51261c0e11288262db604489a4c435802387c83

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

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention cites this paper.

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

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-04T09:20:07.977364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Observation 824085dd-9630-43a3-af45-b7986610acb4 · inbound

RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models cites this paper.

RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-06-29T19:43:54.714408Z

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.

source=pdf_text observed=2026-06-29T19:40:42.033793Z digest=sha256:5b3a3af86bdcdfad113ac0ab92a29c6c0f186a731a10bd254f70362109501994

Observation 9a130e4f-2820-48a8-ae18-aa3d73c92158 · 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 DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-05T20:50:04.029253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:50:04.029253Z digest=sha256:6291e94adbc581af634de7bd6407ad64348c394e4c7f157b4632a13e673e32f8