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Paper Citation Record · LEDGER

Efficient unsupervised domain adaptation via self-supervised vision transformer and synergistic cross-domain alignment

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.21311.

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

pith.paper-citation-record.v1
2407.21311 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:50:33.104572Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T10:51:30.250751Z

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 a0274ada-ea08-42dd-aef6-271e0b2218bb · inbound

Domain Adaptation Techniques for Natural and Medical Image Classification cites this paper.

Domain Adaptation Techniques for Natural and Medical Image Classification Efficient unsupervised domain adaptation via self-supervised vision transformer and synergistic cross-domain alignment

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T16:50:33.104572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:50:33.104572Z digest=sha256:fa75ea61a1a87d407ca83feaa2466c44bd70f3685aedc9d61a8c7bd5dfdea303

Observation f541f0f5-0438-48fe-a70d-343f2f06672a · inbound

Dual-Foundation Models for Unsupervised Domain Adaptation cites this paper.

Dual-Foundation Models for Unsupervised Domain Adaptation Efficient unsupervised domain adaptation via self-supervised vision transformer and synergistic cross-domain alignment

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-08-05T01:36:10.999912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-08T01:34:49.038295Z digest=sha256:db2263e7801aad65ab5ba27a06ca92fb17def8314d2aa7a0dbfefe9d1842ba0a