Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Optimizing News Text Classification with Bi-LSTM and Attention Mechanism for Efficient Data Processing
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.15576.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T17:23:20.671438Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T23:46:09.762483Z
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 5087189f-01fc-4e3a-8313-6c8344198912 · inbound
Graph Neural Network-Based Entity Extraction and Relationship Reasoning in Complex Knowledge Graphs cites this paper.
Graph Neural Network-Based Entity Extraction and Relationship Reasoning in Complex Knowledge Graphs Optimizing News Text Classification with Bi-LSTM and Attention Mechanism for Efficient Data Processing
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T17:23:20.671438Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 40e8828f-30cf-452e-93d0-71b39a5b44ba · inbound
Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data cites this paper.
Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data Optimizing News Text Classification with Bi-LSTM and Attention Mechanism for Efficient Data Processing
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T11:03:15.123103Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90de52a0-50ef-49e5-89e8-1ddf0ae436ef · inbound
An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction cites this paper.
An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction Optimizing News Text Classification with Bi-LSTM and Attention Mechanism for Efficient Data Processing
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T23:46:09.766959Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.