Paper Citation Record · LEDGER

Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2304.14999.

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

pith.paper-citation-record.v1
2304.14999 v1

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 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:48:15.169866Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:56:28.086389Z

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 0a8e7e65-4305-4c2b-b4f9-2f3c495f7e22 · inbound

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

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-13T11:32:36.929373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9732d203-0c24-41af-a9d2-b3b1d655a8f0 · inbound

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding cites this paper.

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.169866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0702b669-d931-47a0-b526-7cb75794843a · inbound

DECA: Decentralizing Block-Wise Adam for Efficient LLM Full-Parameter Fine-Tuning on Non-IID Data cites this paper.

DECA: Decentralizing Block-Wise Adam for Efficient LLM Full-Parameter Fine-Tuning on Non-IID Data Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:56:28.089097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 75aefdf6-d6b6-47b4-a2a1-844689fc5e33 · inbound

Energy- and Memory-Efficient PEFT Methods for Personalized On-Device SLMs on Consumer GPUs cites this paper.

Energy- and Memory-Efficient PEFT Methods for Personalized On-Device SLMs on Consumer GPUs Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:25:09.117752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.