Pith. sign in

Paper Citation Record · LEDGER

Revisiting Fine-tuning for Few-shot Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1910.00216.

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

pith.paper-citation-record.v1
1910.00216 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:13:53.345076Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T13:38:33.390334Z

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 faa0b0ca-54b0-4e5b-8cd0-f09e20489564 · inbound

Exploring Few-Shot Defect Segmentation in General Industrial Scenarios with Metric Learning and Vision Foundation Models cites this paper.

Exploring Few-Shot Defect Segmentation in General Industrial Scenarios with Metric Learning and Vision Foundation Models Revisiting Fine-tuning for Few-shot Learning

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-09T16:13:53.345076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:13:53.345076Z digest=sha256:953d4c562cf6ac0021d5ea57d4608c5e570dcef76c26148f6b60dc5c7b58e0c3

Observation 8cb45dde-e829-43f0-b892-a6ac86f72169 · inbound

Few-Shot Generalized Category Discovery With Retrieval-Guided Decision Boundary Enhancement cites this paper.

Few-Shot Generalized Category Discovery With Retrieval-Guided Decision Boundary Enhancement Revisiting Fine-tuning for Few-shot Learning

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T23:41:12.637348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:41:12.637348Z digest=sha256:764934f32063ed44e739d4f55f39fa8512876cc93084879cd913832aa059f686

Observation 9dba3041-d485-46d1-ab8e-c9ffaa0219d1 · inbound

KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model cites this paper.

KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model Revisiting Fine-tuning for Few-shot Learning

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T17:22:11.496851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:22:11.496851Z digest=sha256:cd15dc7cdef1825d6f932d631d6507eb3b86f534603d601489a7420027a8c27c

Observation 7d236ba4-bc85-4197-aed4-b62904747a05 · inbound

Beyond Class Tokens: LLM-guided Dominant Property Mining for Few-shot Classification cites this paper.

Beyond Class Tokens: LLM-guided Dominant Property Mining for Few-shot Classification Revisiting Fine-tuning for Few-shot Learning

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-06T13:38:33.644682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T13:38:28.515241Z digest=sha256:c305b0ddd983d36632c7f9194b8c43ce5b6100b2a0bc1ec42591305a0062750a