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Paper Citation Record · LEDGER

On Transferability of Prompt Tuning for Natural Language Processing

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2111.06719.

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

pith.paper-citation-record.v1
2111.06719 v2

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 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T05:25:38.967645Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T05:29:48.114657Z

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 44515850-dcdb-41d6-a019-2aadf6fe4a27 · inbound

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey On Transferability of Prompt Tuning for Natural Language Processing

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-13T11:32:36.816162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-13T11:32:36.738536Z digest=sha256:73626d6f36175608c4aa272d89af716c2216e69858e2c9fbaaf9127083f31cfc

Observation 346c9d01-5d66-4cba-a7e3-f86e99af982f · inbound

PEML: Parameter-efficient Multi-Task Learning with Optimized Continuous Prompts cites this paper.

PEML: Parameter-efficient Multi-Task Learning with Optimized Continuous Prompts On Transferability of Prompt Tuning for Natural Language Processing

Reference 85

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:29:48.117889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-15T05:25:38.967645Z digest=sha256:0db4a64c4222cb2b930079c5a2af07db77f6f50d3d1868bb830d28e47ccf96be