Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2404.13506.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T04:24:53.783999Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T14:38:29.313028Z
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 8419d495-bbbf-4758-a041-5a144b2b118b · inbound
Potential and Perils of Large Language Models as Judges of Unstructured Textual Data cites this paper.
Potential and Perils of Large Language Models as Judges of Unstructured Textual Data Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:32:11.163326Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb6c4c00-80f4-4bf7-aea6-1f75dab5cb98 · inbound
IndicMMLU-Pro: Benchmarking Indic Large Language Models on Multi-Task Language Understanding cites this paper.
IndicMMLU-Pro: Benchmarking Indic Large Language Models on Multi-Task Language Understanding Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T14:01:35.921165Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a195317-965e-4942-aa2c-7a452973844d · inbound
Parameter Efficient Fine-Tuning of Segment Anything Model for Biomedical Imaging cites this paper.
Parameter Efficient Fine-Tuning of Segment Anything Model for Biomedical Imaging Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T19:11:00.497606Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c15fe0a-4abe-4576-97dd-8ef9f128f55b · inbound
Can Smaller LLMs do better? Unlocking Cross-Domain Potential through Parameter-Efficient Fine-Tuning for Text Summarization cites this paper.
Can Smaller LLMs do better? Unlocking Cross-Domain Potential through Parameter-Efficient Fine-Tuning for Text Summarization Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:43:41.803961Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1adcae7-9afe-4345-bed2-2dde7ab1dfce · inbound
FMplex: Model Virtualization for Serving Extensible Foundation Models cites this paper.
FMplex: Model Virtualization for Serving Extensible Foundation Models Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T03:47:35.369791Z
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 2c1face4-d1f5-43c2-a5e1-89cf90dfab51 · inbound
Direct Preference Optimization for Chatbot Fine-Tuning: An Empirical Study cites this paper.
Direct Preference Optimization for Chatbot Fine-Tuning: An Empirical Study Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T14:38:29.314374Z
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 2930e22a-e666-403e-b8aa-0f8b745da9b9 · 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 Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:25:09.288553Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6d8bf58b-efbf-4855-acf1-fd80541fcaac · inbound
From Manuals to Maintenance: Fine-Tuning MedGemma for Multi-Modal Imaging System Support in Low-Resource Settings cites this paper.
From Manuals to Maintenance: Fine-Tuning MedGemma for Multi-Modal Imaging System Support in Low-Resource Settings Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:24:53.783999Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.