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Paper Citation Record · LEDGER

Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.14385.

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

pith.paper-citation-record.v1
2104.14385 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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:05:12.214285Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T01:27:02.527330Z

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 9b30cc55-dbbf-4d6f-a66a-f260166674e8 · inbound

Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting cites this paper.

Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-12T05:05:12.214285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:05:12.214285Z digest=sha256:a1afce0896e64f7ecb0b9ff97cc19908a8bd9fb26ef9ac45253b1e84da2036df

Observation 65d43c5e-33c7-454e-8c03-2025b7b3f4d6 · inbound

Reviving In-domain Fine-tuning Methods for Source-Free Cross-domain Few-shot Learning cites this paper.

Reviving In-domain Fine-tuning Methods for Source-Free Cross-domain Few-shot Learning Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:27:02.529742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-13T01:24:22.361181Z digest=sha256:28d6beb65b4f3207cc8da05f183dfbeb1b3e908959301051bd073e37de4a0a56