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Paper Citation Record · LEDGER

Denoising Vision Transformers

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2401.02957.

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

pith.paper-citation-record.v1
2401.02957 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:44:21.158717Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T01:40:52.062182Z

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 7390f044-d4a4-4a46-bffd-2cf64e4fcd16 · inbound

Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning cites this paper.

Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning Denoising Vision Transformers

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T10:13:13.536203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:13:13.536203Z digest=sha256:f7681312fe493aba172c6c5fcb26df7d36a4cc6ac1456bec28461beca9bbb06f

Observation aa69e7fb-c00a-4641-b9f4-831a8d05ddce · inbound

Retrieval Augmented Image Harmonization cites this paper.

Retrieval Augmented Image Harmonization Denoising Vision Transformers

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T12:44:18.700607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:44:18.700607Z digest=sha256:a727453f485443576260ca5c5a158fd889b60a116250c9beb7d4d311106d038b

Observation 0f38c679-ce8a-41a5-9dbd-e37c28aced91 · inbound

Incorporating Feature Pyramid Tokenization and Open Vocabulary Semantic Segmentation cites this paper.

Incorporating Feature Pyramid Tokenization and Open Vocabulary Semantic Segmentation Denoising Vision Transformers

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T12:28:54.658445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:28:54.658445Z digest=sha256:3b42c3772939f6af0a91db01c3166a76b680752abdc2e48777ceb5f98222df28

Observation 14cdf7e4-2780-454a-a415-fefcdba6bcf5 · inbound

Rethinking Encoder-Decoder Flow Through Shared Structures cites this paper.

Rethinking Encoder-Decoder Flow Through Shared Structures Denoising Vision Transformers

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-10T15:06:59.564819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:06:59.564819Z digest=sha256:28bd824613f22b812f177fed10a2bf89cffee1c5141af7a75fe0135e2ba053ed

Observation db952d83-25e4-4407-a61f-19927d03e5f1 · inbound

Maybe you don't need a U-Net: convolutional feature upsampling for materials micrograph segmentation cites this paper.

Maybe you don't need a U-Net: convolutional feature upsampling for materials micrograph segmentation Denoising Vision Transformers

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-15T16:44:21.158717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:44:21.158717Z digest=sha256:2802d10423d570e502ea41a5684f8af75baa2bb0dcdeb7afac9ddd40deb83b8e

Observation f1a8e71a-e0ff-4bc3-8e55-dbab86f0623c · inbound

LookWhen? Fast Video Recognition by Learning When, Where, and What to Compute cites this paper.

LookWhen? Fast Video Recognition by Learning When, Where, and What to Compute Denoising Vision Transformers

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-11T01:40:52.064300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-11T01:36:50.406353Z digest=sha256:810c3822c51780c73f7c0d4d5f5961d17108cf270924cf166b881a4f471c9e92