Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2311.03748.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:59:48.054528Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T11:32:36.893255Z
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 bb890ca1-855f-4a75-89eb-c9eee40ed0f4 · inbound
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning
Reference 67
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T11:32:36.894757Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 97ae2282-ecd5-49ce-ab71-39b31d6acfad · inbound
Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges cites this paper.
Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning
Reference 122
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T22:41:17.719115Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 420d26a3-864e-42e0-a457-790519ffc06c · inbound
Refining Salience-Aware Sparse Fine-Tuning Strategies for Language Models cites this paper.
Refining Salience-Aware Sparse Fine-Tuning Strategies for Language Models Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T13:08:44.071767Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d52919f-05ce-44e3-984a-3f6645c51f7c · inbound
PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models cites this paper.
PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning
Reference 125
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:59:48.054528Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d66a7e00-af97-493b-aaa5-77317cd53982 · inbound
GEM: A Scale-Aware and Distribution-Sensitive Sparse Fine-Tuning Framework for Effective Downstream Adaptation cites this paper.
GEM: A Scale-Aware and Distribution-Sensitive Sparse Fine-Tuning Framework for Effective Downstream Adaptation Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:33:13.475037Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.