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Paper Citation Record · LEDGER

Deep Visual Domain Adaptation: A Survey

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1802.03601.

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

pith.paper-citation-record.v1
1802.03601 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:57:13.652486Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T01:37:22.560937Z

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 0b672304-22f0-4291-a605-294822a87c1a · inbound

Towards a Problem-Oriented Domain Adaptation Framework for Machine Learning cites this paper.

Towards a Problem-Oriented Domain Adaptation Framework for Machine Learning Deep Visual Domain Adaptation: A Survey

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T21:35:08.547484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:35:08.547484Z digest=sha256:d67c64c1b102a569de31a873c363be49b49c5ecdfd38ae5cdbf47e35f243c5a2

Observation 1af5a7ca-4518-4897-b0e3-cce8d61f5081 · inbound

Unsupervised Source-Free Ranking of Biomedical Segmentation Models Under Distribution Shift cites this paper.

Unsupervised Source-Free Ranking of Biomedical Segmentation Models Under Distribution Shift Deep Visual Domain Adaptation: A Survey

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:37:22.565057Z

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=2026-05-23T01:36:12.509353Z digest=sha256:aa8c039b8ba861e2627babed529e221b83a32bf3752c56e865e3f9d9a6922947

Observation 7378a023-daa3-4c4f-b3b1-6fd111207434 · inbound

UNIFORM: Unifying Knowledge from Large-scale and Diverse Pre-trained Models cites this paper.

UNIFORM: Unifying Knowledge from Large-scale and Diverse Pre-trained Models Deep Visual Domain Adaptation: A Survey

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-15T16:57:13.652486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:57:13.652486Z digest=sha256:c262c8cd94c4ba137b1189bb7049c1d10ef863e25c106188c4aab6389cb9c089