Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.02638.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:22:29.739746Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T21:22:29.996911Z
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 af378e94-12d5-44a3-8edc-bcb63fe78e31 · 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 Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T21:22:30.000173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation c976d5a1-c1ac-49c9-9065-93511c3203b6 · inbound
CCoMAML: Efficient Cattle Identification Using Cooperative Model-Agnostic Meta-Learning cites this paper.
CCoMAML: Efficient Cattle Identification Using Cooperative Model-Agnostic Meta-Learning Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:57:31.950724Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.