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Paper Citation Record · LEDGER

Masked Diffusion as Self-supervised Representation Learner

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2308.05695.

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

pith.paper-citation-record.v1
2308.05695 v4

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 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:02:08.474142Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:36:24.479933Z

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 4d9fe173-a6d5-47a5-8d19-b41a48e1c51e · inbound

MetaFE-DE: Learning Meta Feature Embedding for Depth Estimation from Monocular Endoscopic Images cites this paper.

MetaFE-DE: Learning Meta Feature Embedding for Depth Estimation from Monocular Endoscopic Images Masked Diffusion as Self-supervised Representation Learner

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-09T10:59:44.246625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:59:44.246625Z digest=sha256:25de08dcd29ed2949dcd6e045b7b71e4f70851cacbafeea82f3ef83a57d42759

Observation 03fd2802-ee72-4f28-b859-3454c243b07f · inbound

Less is More: Masking Elements in Image Condition Features Avoids Content Leakages in Style Transfer Diffusion Models cites this paper.

Less is More: Masking Elements in Image Condition Features Avoids Content Leakages in Style Transfer Diffusion Models Masked Diffusion as Self-supervised Representation Learner

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-08T12:49:57.523535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T12:49:57.523535Z digest=sha256:098720bc1aa35ac30f5893022deeab6e3a99bcdc3fdcc4bccc7a7de8841a510e

Observation de63d4e9-3ce4-4ea9-a7f0-2a5a4cc1258e · inbound

Automated Learning of Semantic Embedding Representations for Diffusion Models cites this paper.

Automated Learning of Semantic Embedding Representations for Diffusion Models Masked Diffusion as Self-supervised Representation Learner

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T23:02:08.474142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:02:08.474142Z digest=sha256:0e5cca0b58b7bffa02ecd98ddb078cbcc0acbf69737024194dfcf7b4824ac7d6

Observation 8720d902-17fb-400f-a47c-65e9619a8138 · inbound

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction cites this paper.

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction Masked Diffusion as Self-supervised Representation Learner

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:36:24.482967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-12T00:58:28.390860Z digest=sha256:e278c01b72a843224589364affc7e504861780c3aaa9b9aa6755980cf0c17a3c