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Paper Citation Record · LEDGER

Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2307.03042.

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

pith.paper-citation-record.v1
2307.03042 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:36:08.082526Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T04:13:53.161022Z

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 575f7fcc-0e11-4ab1-b1fd-838a660c47ff · inbound

Data-Centric Foundation Models in Computational Healthcare: A Survey cites this paper.

Data-Centric Foundation Models in Computational Healthcare: A Survey Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain

Reference 95

Resolution
verified exact
arxiv_id, observed 2026-05-24T04:13:53.163470Z

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=2026-05-24T04:13:05.328492Z digest=sha256:0c78860bed36f36a5001249d3a7043b752a76631c3ae7ecac666c7e9752e5425

Observation e6310e21-0dfd-441a-b732-b1a6c51caa06 · inbound

ELMTEX: Fine-Tuning Large Language Models for Structured Clinical Information Extraction. A Case Study on Clinical Reports cites this paper.

ELMTEX: Fine-Tuning Large Language Models for Structured Clinical Information Extraction. A Case Study on Clinical Reports Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-08T18:36:08.082526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:36:08.082526Z digest=sha256:3dea6ab37f845ed69579237ce05bd26119813f1c846d44f816dfc5364f03fc22

Observation 78865775-a7b6-4d8b-a38d-51be5ae4aba3 · inbound

Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race cites this paper.

Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T12:13:15.219580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:13:15.219580Z digest=sha256:b96ec182a0ca424deaa1af9f2dd5fb032fbcbccbe072219422a3e44848d3ea91