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Paper Citation Record · LEDGER

Optimized Generic Feature Learning for Few-shot Classification across Domains

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2001.07926.

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

pith.paper-citation-record.v1
2001.07926 v1

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:48:07.644311Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:22:29.985915Z

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 f24c85ac-f94c-42af-8fa1-3e25c3359690 · inbound

Reliable Few-shot Learning under Dual Noises cites this paper.

Reliable Few-shot Learning under Dual Noises Optimized Generic Feature Learning for Few-shot Classification across Domains

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-06T23:48:07.644311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:48:07.644311Z digest=sha256:0d32fbfaa09b753710e141527a30ca0e823e948788423d121697040dd1cbe9c8

Observation 14c84a2e-ba96-413a-9b8c-55ea25e9db11 · inbound

Few-shot Classification as Multi-instance Verification: Effective Backbone-agnostic Transfer across Domains cites this paper.

Few-shot Classification as Multi-instance Verification: Effective Backbone-agnostic Transfer across Domains Optimized Generic Feature Learning for Few-shot Classification across Domains

Reference 54

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:22:29.990040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T21:22:29.837104Z digest=sha256:30f2dee5e007870da52f15b7882b94602b1ae236152a4470e3a55589d3f69c4f