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Paper Citation Record · LEDGER

Domain-Adversarial Neural Networks

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1412.4446.

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

pith.paper-citation-record.v1
1412.4446 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-24T20:25:16.705014Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-24T20:26:20.980569Z

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 ffbe6e7d-80b1-40f7-8a96-76990e8e3f22 · inbound

Concrete Problems in AI Safety cites this paper.

Concrete Problems in AI Safety Domain-Adversarial Neural Networks

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:16:32.855324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-11T05:16:31.970352Z digest=sha256:ba8e6d8b0cf6c18cb555600128af6ed4437ff09588e7aac6ae073f0683d27139

Observation d87af4e2-f9a3-4827-b288-0186dc482353 · inbound

Remaining Useful Lifetime Prediction via Deep Domain Adaptation cites this paper.

Remaining Useful Lifetime Prediction via Deep Domain Adaptation Domain-Adversarial Neural Networks

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-05-24T20:26:20.983025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-24T20:25:16.705014Z digest=sha256:77e27e438732515beda9d6d30ec2cf7a6f08c1bff8938120e91be0d4f9203f88

Observation f1fff226-a2bc-4e22-98f4-4f97de33adf9 · inbound

Multi-Purposing Domain Adaptation Discriminators for Pseudo Labeling Confidence cites this paper.

Multi-Purposing Domain Adaptation Discriminators for Pseudo Labeling Confidence Domain-Adversarial Neural Networks

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-05-24T20:14:52.938342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-24T20:13:33.776091Z digest=sha256:9442dcf7219c27e3f3122fdfbdca7b694c4fc63459892cb0ad245b2e73bd1e72

Observation 54235055-b9af-472c-8814-625da86b49ff · inbound

DisRFM: Polar Riemannian Flow Matching for Structure-Preserving Graph Domain Adaptation cites this paper.

DisRFM: Polar Riemannian Flow Matching for Structure-Preserving Graph Domain Adaptation Domain-Adversarial Neural Networks

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-05-16T09:07:39.226167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T09:04:27.194613Z digest=sha256:278fa842aa9dc311f9759e864e55557608e940a467177e40288e405fc7394e92

Observation 054f9efb-c27a-4768-a27e-0966ab2842d0 · inbound

CrossFlowDG: Bridging the Modality Gap with Cross-modal Flow Matching for Domain Generalization cites this paper.

CrossFlowDG: Bridging the Modality Gap with Cross-modal Flow Matching for Domain Generalization Domain-Adversarial Neural Networks

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-10T07:52:13.806202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T07:48:03.572543Z digest=sha256:5774e94cfc846da46d7c563967e1a6df2a718e72e05fe92c8aed87a636ed7c96