Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Survey of Active Learning for Text Classification using Deep Neural Networks
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2008.07267.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T11:05:09.717696Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T10:56:30.280370Z
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 4a99e5d9-0fa5-49f1-8fc0-587f57715fe5 · inbound
Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study cites this paper.
Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study A Survey of Active Learning for Text Classification using Deep Neural Networks
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T11:05:09.717696Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f29c801-65cb-4fa8-abdf-b8b08f291051 · inbound
The Power of Adaptation: Boosting In-Context Learning through Adaptive Prompting cites this paper.
The Power of Adaptation: Boosting In-Context Learning through Adaptive Prompting A Survey of Active Learning for Text Classification using Deep Neural Networks
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:21:05.181812Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7be83e4c-a9e3-45c7-aa4f-e812fa263cd4 · inbound
Retrieving Floods without Floodlights: Topic Models as Binary Classifiers for Extreme Climate Events in German News cites this paper.
Retrieving Floods without Floodlights: Topic Models as Binary Classifiers for Extreme Climate Events in German News A Survey of Active Learning for Text Classification using Deep Neural Networks
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:56:30.282864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.