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Paper Citation Record · LEDGER

Semi-supervised Domain Adaptation via Minimax Entropy

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.06487.

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

pith.paper-citation-record.v1
1904.06487 v5

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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:26:20.623455Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T05:43:57.261224Z

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 eecc1827-b1b2-4696-ba6f-23f9ffffa35d · inbound

Dynamic Scale Inference by Entropy Minimization cites this paper.

Dynamic Scale Inference by Entropy Minimization Semi-supervised Domain Adaptation via Minimax Entropy

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-14T14:26:20.623455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:26:20.623455Z digest=sha256:33dcda5a29809e3878899419563a39b88125d1bbfe05df1076e46cea79128019

Observation b0250e45-f31f-4160-bffe-def23f263ead · inbound

Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation cites this paper.

Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation Semi-supervised Domain Adaptation via Minimax Entropy

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-14T05:43:57.269175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-14T05:43:57.105056Z digest=sha256:94a5856a5c962a045c87167e802ed2a8c675afa3a60258e9532b4a7af3c9f97d