Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Time Series Feature Redundancy Paradox: An Empirical Study Based on Mortgage Default Prediction
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.00034.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T15:57:30.288766Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-08T21:44:20.397458Z
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 99669315-58ca-4607-9156-4723ce9353c3 · inbound
Multi-Level Attention and Contrastive Learning for Enhanced Text Classification with an Optimized Transformer cites this paper.
Multi-Level Attention and Contrastive Learning for Enhanced Text Classification with an Optimized Transformer Time Series Feature Redundancy Paradox: An Empirical Study Based on Mortgage Default Prediction
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:57:30.288766Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dc0ce2b3-4d9b-422c-9e7c-477489531466 · inbound
Dynamic Adaptation of LoRA Fine-Tuning for Efficient and Task-Specific Optimization of Large Language Models cites this paper.
Dynamic Adaptation of LoRA Fine-Tuning for Efficient and Task-Specific Optimization of Large Language Models Time Series Feature Redundancy Paradox: An Empirical Study Based on Mortgage Default Prediction
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T14:55:04.093724Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5d4bd330-a7e5-487f-aa48-c05aee5be562 · inbound
A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction cites this paper.
A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Time Series Feature Redundancy Paradox: An Empirical Study Based on Mortgage Default Prediction
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T21:44:20.404434Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.