Paper Citation Record · LEDGER

Learning to Compare: Relation Network for Few-Shot Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1711.06025.

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

pith.paper-citation-record.v1
1711.06025 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 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:57:23.578688Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-24T20:49:54.560285Z

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 46e3c302-20da-4009-a023-7e36c31fb896 · inbound

How much real data do we actually need: Analyzing object detection performance using synthetic and real data cites this paper.

How much real data do we actually need: Analyzing object detection performance using synthetic and real data Learning to Compare: Relation Network for Few-Shot Learning

Reference 13

Resolution: metadata mismatch; local_arxiv, observed 2026-05-24T20:49:54.563592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f543cbb9-8765-4033-a105-6924701708ee · inbound

Adaptive Few-Shot Learning (AFSL): Tackling Data Scarcity with Stability, Robustness, and Versatility cites this paper.

Adaptive Few-Shot Learning (AFSL): Tackling Data Scarcity with Stability, Robustness, and Versatility Learning to Compare: Relation Network for Few-Shot Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T15:57:23.578688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca067580-af3b-4692-a80a-12dadc209739 · inbound

ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation cites this paper.

ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation Learning to Compare: Relation Network for Few-Shot Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T18:06:31.299308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8272a54e-7cf3-4a3c-b509-3c7578aa1c9c · inbound

Scaling Up Audio-Synchronized Visual Animation: An Efficient Training Paradigm cites this paper.

Scaling Up Audio-Synchronized Visual Animation: An Efficient Training Paradigm Learning to Compare: Relation Network for Few-Shot Learning

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T01:05:33.421342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1380b478-461d-4076-8717-5a0c94a3e79c · inbound

Rethinking the Good Enough Embedding for Easy Few-Shot Learning cites this paper.

Rethinking the Good Enough Embedding for Easy Few-Shot Learning Learning to Compare: Relation Network for Few-Shot Learning

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-15T04:59:45.989427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.