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Paper Citation Record · LEDGER

PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen Domains

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2102.12206.

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

pith.paper-citation-record.v1
2102.12206 v4

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-24T09:43:26.288866Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T09:43:26.383009Z

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 eb41966b-211c-42fe-badf-fda1338307c9 · inbound

Cross-Task Generalization via Natural Language Crowdsourcing Instructions cites this paper.

Cross-Task Generalization via Natural Language Crowdsourcing Instructions PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen Domains

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T01:57:29.499816Z

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.

source=arxiv_source observed=2026-05-18T01:57:29.380571Z digest=sha256:6083f8a4b512cf8e7f7270fc394e03f72b5031440f48bcb02dc037962a49faf4

Observation 3bbd9569-5682-4d1a-ac99-87f9839660a1 · inbound

Large Language Models Are Human-Level Prompt Engineers cites this paper.

Large Language Models Are Human-Level Prompt Engineers PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen Domains

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-24T09:43:26.385774Z

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.

source=pdf_text observed=2026-05-24T09:43:26.288866Z digest=sha256:d2ba1a61163544f9e8b3b56f4fe8f545549b69f3befeea50fcf5cb13a52fd41c