Paper Citation Record · LEDGER

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction

As of 23 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 1 inbound Pith citation observation for arXiv:2502.06847.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.06847 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:44:20.363765Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:35:13.109402Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-16T11:35:13.265742Z

Reference resolution

22 of 22 outbound references displayed

verified exact2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b1534c4d-f235-4531-a457-4506dc6f60fd · outbound

This paper cites Analyze the Impact of the Epidemic on New York Taxis by Machine Learning Algorithms and Recommendations for Optimal Prediction Algorithms,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Analyze the Impact of the Epidemic on New York Taxis by Machine Learning Algorithms and Recommendations for Optimal Prediction Algorithms,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.715653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8aeaeca4-0b7f-43cd-bd35-398869d0c4d7 · outbound

This paper cites Investigation of the Influence of Non -Routine and Derived Features in the Development of Early Detection Model for Transformer Health Index Classification.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Investigation of the Influence of Non -Routine and Derived Features in the Development of Early Detection Model for Transformer Health Index Classification

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.700150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d9bc9a6d-c213-4c3a-931c-929fb754fe5d · outbound

This paper cites Accounting Management and Optimizing Production Based on Distributed Semantic Recognition.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Accounting Management and Optimizing Production Based on Distributed Semantic Recognition

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.685544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9bd630fc-58e5-47a5-8dfa-588b9ae6dc4d · outbound

This paper cites A Stock Price Prediction Method Based on Bi-LSTM and Improved Transformer.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction A Stock Price Prediction Method Based on Bi-LSTM and Improved Transformer

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.671026Z

Source-reported events for the cited work

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Observation 027572a8-2a1d-4457-962b-385d32a4b273 · outbound

This paper cites Integrating Deep Transformer and Temporal Convolutional Networks for SMEs Revenue and Employment Growth Prediction.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Integrating Deep Transformer and Temporal Convolutional Networks for SMEs Revenue and Employment Growth Prediction

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.656848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a2eb58e7-9d32-4f42-8731-26904d649f12 · outbound

This paper cites Calibration Learning for Few -shot Novel Product Description,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Calibration Learning for Few -shot Novel Product Description,

Reference 6

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Source-reported events for the cited work

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Observation 47225cf2-b0ae-4448-ab07-48f4af287052 · outbound

This paper cites Adaptive Receptive Field U -Shaped Temporal Convolutional Network for Vulgar Action Segmentation,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Adaptive Receptive Field U -Shaped Temporal Convolutional Network for Vulgar Action Segmentation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.632062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 748ef496-dc14-4404-abb8-ae18afdf8bd0 · outbound

This paper cites Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining

Reference 8

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Source-reported events for the cited work

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Observation 078cbdad-24d0-4d86-bb8a-50d43990451a · outbound

This paper cites Optimized Convolutional Neural Network for Intelligent Financial Statement Anomaly Detection,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Optimized Convolutional Neural Network for Intelligent Financial Statement Anomaly Detection,

Reference 9

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Source-reported events for the cited work

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Observation 707ebd74-a797-4a80-8250-d8ec39569487 · outbound

This paper cites Integrative Analysis of Financial Market Sentiment Using CNN and GRU for Risk Prediction and Alert Systems,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Integrative Analysis of Financial Market Sentiment Using CNN and GRU for Risk Prediction and Alert Systems,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.607234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8ba3ceaa-bc0e-4e59-8dd1-ced6f4fc9ccd · outbound

This paper cites An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-08T21:44:20.425255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3324d4f3-5535-4f7f-ab3f-d6241c17d0b3 · outbound

This paper cites Time -Series Nested Reinforcement Learning for Dynamic Risk Control in Nonlinear Financial Markets,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Time -Series Nested Reinforcement Learning for Dynamic Risk Control in Nonlinear Financial Markets,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.592677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5d4bd330-a7e5-487f-aa48-c05aee5be562 · outbound

This paper cites Time Series Feature Redundancy Paradox: An Empirical Study Based on Mortgage Default Prediction.

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 2026-08-22T06:32:14.747728+00:00.

Observation d432347c-4257-4b61-b122-9a762751b0f5 · outbound

This paper cites Adaptive Transaction Sequence Neural Network for Enhanced Money Laundering Detection,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Adaptive Transaction Sequence Neural Network for Enhanced Money Laundering Detection,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.572371Z

Source-reported events for the cited work

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Observation 20f43ba4-4022-460a-957f-21fffe793848 · outbound

This paper cites The Synergistic Role of Deep Learning and Neural Architecture Search in Advancing Artificial Intelligence,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction The Synergistic Role of Deep Learning and Neural Architecture Search in Advancing Artificial Intelligence,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.558262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1970d491-f02d-4f88-b489-fa567904108b · outbound

This paper cites Few -Shot Learning with Adaptive Weight Masking in Conditional GANs,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Few -Shot Learning with Adaptive Weight Masking in Conditional GANs,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.544011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ab99ea18-8096-40fb-822d-63a41e878124 · outbound

This paper cites Stock Type Prediction Model Based on Hierarchical Graph Neural Network,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Stock Type Prediction Model Based on Hierarchical Graph Neural Network,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.529225Z

Source-reported events for the cited work

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Observation 181be4a2-05c8-4ab9-b6ed-acfd28dcdc24 · outbound

This paper cites Fine -Grained Imbalanced Leukocyte Classification With Global -Local Attention Transformer,.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Fine -Grained Imbalanced Leukocyte Classification With Global -Local Attention Transformer,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.513461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 49ecf3fe-c58d-42f7-8685-4f571086dcd6 · outbound

This paper cites Investigation of Creating Accessibility Linked Data Based on Publicly Available Accessibility Datasets.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Investigation of Creating Accessibility Linked Data Based on Publicly Available Accessibility Datasets

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.499145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bb1bb243-7f38-43ef-bc64-ac7a1148255c · outbound

This paper cites Optimizing Bidirectional Long Short - Term Memory Networks for Univariate Time Series Forecasting: A Comprehensive Guide.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Optimizing Bidirectional Long Short - Term Memory Networks for Univariate Time Series Forecasting: A Comprehensive Guide

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.485020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4c5baa5d-c19a-4daa-918f-1de8a9a636d2 · outbound

This paper cites Enhancing Supply Chain Resilience: A Deep Learning Approach to Late Delivery Risk Prediction.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction Enhancing Supply Chain Resilience: A Deep Learning Approach to Late Delivery Risk Prediction

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.470630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8feb6564-670e-46b8-bed3-c57f261c288f · outbound

This paper cites A Gold Price Prediction Model Based on Economic Indicators Using Temporal Convolution and Attention Mechanism.

A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction A Gold Price Prediction Model Based on Economic Indicators Using Temporal Convolution and Attention Mechanism

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:44:20.456353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation 2ce23a84-0083-475e-a82f-d1bc7723eb7c · inbound

A Deep Learning Framework for Sequence Mining with Bidirectional LSTM and Multi-Scale Attention cites this paper.

A Deep Learning Framework for Sequence Mining with Bidirectional LSTM and Multi-Scale Attention A Deep Learning Framework Integrating CNN and BiLSTM for Financial Systemic Risk Analysis and Prediction

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-16T11:35:13.272612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.