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Paper Citation Record · LEDGER

CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2412.16112.

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

pith.paper-citation-record.v1
2412.16112 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T22:37:42.076990Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T04:49:44.350666Z

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 ee90d107-e3d7-4b05-a824-932df35c9935 · inbound

Fast Video Generation with Sliding Tile Attention cites this paper.

Fast Video Generation with Sliding Tile Attention CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T22:37:42.076990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T22:37:42.076990Z digest=sha256:92e5bd5d0466252d7ef5208e64fc49b3df4b577ed412a56f2106df430271f8e5

Observation 35b85fd9-8839-4faa-a332-90f6e4ea280d · inbound

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers cites this paper.

Grouping First, Attending Smartly: Training-Free Acceleration for Diffusion Transformers CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T15:33:10.540296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:33:10.540296Z digest=sha256:a274088f5343c1d06882164a26abb304aa17486f27415e1921f0cdbab8a15b5e

Observation 78d5b7f4-987c-41d8-8fff-0866a7dab333 · inbound

Long-Context State-Space Video World Models cites this paper.

Long-Context State-Space Video World Models CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T14:03:17.722525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:03:17.722525Z digest=sha256:1831a8d37b753e1c2c0b501df637048065e6412684dc8faf2359c4615817a6b1

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

source=pdf_text observed=2026-08-07T11:15:16.170658Z digest=sha256:8f2f180675fcb45e7331ab7b558deb262f416b5d7b9a1aee42bd7a4df8b6e53e

Observation 08c57e6b-7b12-4d86-878d-6a1237331c3a · inbound

Exploring Diffusion Transformer Designs via Grafting cites this paper.

Exploring Diffusion Transformer Designs via Grafting CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T10:29:04.559699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:29:04.559699Z digest=sha256:483dba54721953866da893ac1ea6cfe33f8f29766c605af19bd88d61b9ae7bfa

Observation f43143fe-743a-4133-9c89-30880657aac2 · inbound

LSSGen: Leveraging Latent Space Scaling in Flow and Diffusion for Efficient Text to Image Generation cites this paper.

LSSGen: Leveraging Latent Space Scaling in Flow and Diffusion for Efficient Text to Image Generation CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T15:22:26.319986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:22:26.319986Z digest=sha256:6e8dd58d7b10454618ff006f2c54172bdd3e1c30c376496b5715c058962c827b

Observation 4c234ab7-1ce2-4bd1-afbf-988e6a20e5ad · inbound

MatchAttention: Embedding Explicit Matching Constraints into Attention for Efficient Stereo Matching cites this paper.

MatchAttention: Embedding Explicit Matching Constraints into Attention for Efficient Stereo Matching CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-04T09:40:30.003576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:40:30.003576Z digest=sha256:50cf1b615aa93ce43c5eb09e866e8dc7082e5b211f61a47ebac168518e901770

Observation cc50726c-6815-4b30-bf52-a28e30d53595 · inbound

UltraFlux: Data-Model Co-Design for High-quality Native 4K Text-to-Image Generation across Diverse Aspect Ratios cites this paper.

UltraFlux: Data-Model Co-Design for High-quality Native 4K Text-to-Image Generation across Diverse Aspect Ratios CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-03T20:52:38.436119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:52:38.436119Z digest=sha256:9877675a547ea1a76df4ca32b08e66d8fde132fb4a48b3c1cfebe05005919450

Observation 0edbb81d-4ec5-49fd-9a5a-f042d4706505 · inbound

Linearizing Vision Transformer with Test-Time Training cites this paper.

Linearizing Vision Transformer with Test-Time Training CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T06:25:48.635059Z

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=2026-05-08T18:25:48.672665Z digest=sha256:3ee886f8e855d8dc0519282dea9150e61a9876b0c5dff7f32d65e4ecc4e9f73c

Observation 720c137d-6534-4634-bf8d-eea77eba189e · inbound

CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers cites this paper.

CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-15T04:49:44.353981Z

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=2026-05-15T04:47:32.476614Z digest=sha256:b3e1ebc3330848023a95abdfa4b8ad6399d9b50819bda48ab0464db7945f4f5d