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Paper Citation Record · LEDGER

$k$NN-Adapter: Efficient Domain Adaptation for Black-Box Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.10879.

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

pith.paper-citation-record.v1
2302.10879 v1

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:40:25.154848Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T23:08:35.572943Z

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 707ad8c4-c639-4799-95f0-01419acc2da2 · inbound

Retrieval-Augmented Generation for Natural Language Processing: A Survey cites this paper.

Retrieval-Augmented Generation for Natural Language Processing: A Survey $k$NN-Adapter: Efficient Domain Adaptation for Black-Box Language Models

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-05-23T23:08:35.574768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T23:06:41.081461Z digest=sha256:46cece0560726106557d8bc766e5089aa1ff147c0aca7cc21996c82839fb1d5e

Observation c681321b-25d0-4ae3-aa35-cdf10623bde8 · inbound

Minifinetuning: Low-Data Generation Domain Adaptation through Corrective Self-Distillation cites this paper.

Minifinetuning: Low-Data Generation Domain Adaptation through Corrective Self-Distillation $k$NN-Adapter: Efficient Domain Adaptation for Black-Box Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T12:40:25.154848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:25.154848Z digest=sha256:557ba0af9b572f65e54430516ef352b771f075d1986190226ac97025ee4b4d43