Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2410.19878.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:43:23.358774Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T12:44:39.957797Z
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 a2ae0ec1-7fa4-471c-ab8e-07e573144a68 · inbound
Unveiling Instruction-Specific Neurons & Experts: An Analytical Framework for LLM's Instruction-Following Capabilities cites this paper.
Unveiling Instruction-Specific Neurons & Experts: An Analytical Framework for LLM's Instruction-Following Capabilities Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:43:23.358774Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 87bd92fd-8797-4bc4-8430-1afcc0191bb7 · inbound
The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training cites this paper.
The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T00:45:50.660773Z
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.
Observation edff6a8c-4674-4f00-a191-77c01506d2f7 · inbound
DriftGuard: Safety-Aware Multi-Monitor Detection and Selective Adaptation for Evolving Toxicity Moderation cites this paper.
DriftGuard: Safety-Aware Multi-Monitor Detection and Selective Adaptation for Evolving Toxicity Moderation Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T12:44:39.959377Z
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.
Observation 7a68518f-ad23-4ef1-b412-9e09bc81d1d4 · inbound
Little Brains, Big Feats: Exploring Compact Language Models cites this paper.
Little Brains, Big Feats: Exploring Compact Language Models Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T06:24:19.335615Z
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.
Observation 606f1a5f-4352-4304-828e-39508d45c43a · inbound
Data-Efficient Adaptation of LLMs via Attention Head Reweighting cites this paper.
Data-Efficient Adaptation of LLMs via Attention Head Reweighting Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T05:16:37.830928Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4368209-2ed1-4682-ac83-42058e457b84 · inbound
ZMIS-SAM: Segment Anything Model Enhanced with Wavelet Transform for Zooplankton Microscopy Image Instance Segmentation cites this paper.
ZMIS-SAM: Segment Anything Model Enhanced with Wavelet Transform for Zooplankton Microscopy Image Instance Segmentation Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T05:13:23.595056Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b875ad6-5590-4349-8c7b-a8afcb801813 · inbound
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs cites this paper.
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T03:50:58.753155Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.