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Paper Citation Record · LEDGER

DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2308.06160.

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

pith.paper-citation-record.v1
2308.06160 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:39:24.859169Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T20:39:25.693015Z

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 3d3ba372-c395-4d81-85a3-c03ae11ea2da · inbound

Understanding Trade offs When Conditioning Synthetic Data cites this paper.

Understanding Trade offs When Conditioning Synthetic Data DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:39:25.775023Z

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=2026-08-06T20:39:24.859169Z digest=sha256:37280eaf1c1745a2d7a405066c82347fa763ac623bba4f79c1c2ab266043a9ac

Observation 39d923be-154f-4aa4-8bae-ac2f3f84ae69 · inbound

S3OD: Towards Generalizable Salient Object Detection with Synthetic Data cites this paper.

S3OD: Towards Generalizable Salient Object Detection with Synthetic Data DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-04T08:20:01.900714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T08:20:01.900714Z digest=sha256:6dcbb70676f16614ef579e4a5f65ded0570567f394a35be5be02b3df2d769891