Pith. sign in

Paper Citation Record · LEDGER

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data

As of 10 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2502.03803.

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

pith.paper-citation-record.v1
2502.03803 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:42:49.738129Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

  • verified exact3
  • verified fuzzy14
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8b979788-7301-44ce-b2c6-1b694e303073 · outbound

This paper cites Credit Default Prediction with Machine Learning: A Comparative Study and Interpretability Insights,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Credit Default Prediction with Machine Learning: A Comparative Study and Interpretability Insights,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:50.120516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.628573Z digest=sha256:567ac55d8c7ad4b53538e9efe43de353fbf62a654a240ad33a14303ec9aa9316

Observation 2ced5a84-f2bc-4332-aea9-d8d5458d17c8 · outbound

This paper cites Dynamic Risk Control and Asset Allocation Using Q-Learning in Financial Markets,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Dynamic Risk Control and Asset Allocation Using Q-Learning in Financial Markets,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:50.106699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.633955Z digest=sha256:639a9b6cbf90c9008c705754bdd3cdc15d9b6f1ae7bc9feb59ed4dffa7b63ea5

Observation 20e14791-c497-4d7e-aef6-0922c04e112c · outbound

This paper cites Artificial Intelligence- Driven Risk Assessment and Control in Financial Derivatives: Exploring Deep Learning and Ensemble Models,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Artificial Intelligence- Driven Risk Assessment and Control in Financial Derivatives: Exploring Deep Learning and Ensemble Models,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:50.092659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.638796Z digest=sha256:e567a9f221e1e77821ec7eb76b08e92b65f0389934e46e4b52019244385a5b6e

Observation 095d2752-67b6-48e0-9097-e3c44a703aea · outbound

This paper cites Object Detection for Medical Image Analysis: Insights from the RT-DETR Model,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Object Detection for Medical Image Analysis: Insights from the RT-DETR Model,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:50.078443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.643542Z digest=sha256:84ec11bab3f34492cc7b2d0ef5d55ef155f9887c27f6bea133762748eb29beb5

Observation 9289b82f-2607-4fa1-8acf-2ab639cfe17c · outbound

This paper cites Self- Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Self- Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-09T00:42:49.649039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:42:49.649039Z digest=sha256:cb4ea3ca315e93eafc19eecab3a007cd84affc77df8fb13bf29dcf0c4c42af89

Observation 98843717-e180-4884-83d2-690e59061e6d · outbound

This paper cites Learning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Learning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-09T00:42:49.911710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.653826Z digest=sha256:e9a42dcd851effd0872c71defc91f5f59e41a2997d857175ba4a185d531d88a6

Observation a86e00ad-3822-4aa7-ab79-b038848cf176 · outbound

This paper cites Intrusion detection system using statistical query tree with hierarchical clustering approach,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Intrusion detection system using statistical query tree with hierarchical clustering approach,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:50.055040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.658830Z digest=sha256:8cb798d0ee1c946d3b2f18087e9f690052a2f2eeb1c00b390ca711bb7ef3161a

Observation 9233c597-c927-46a8-bddb-7f280122f8b4 · outbound

This paper cites Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi-Supervised Classification.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi-Supervised Classification

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-09T00:42:49.889791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.663589Z digest=sha256:16a37e39bd6734f36589af8ef268951af3abffd3056dd82fe377bff486db8ead

Observation 7f8d65fa-c7a0-4aea-a00e-af639fb8c9df · outbound

This paper cites Data mining techniques for effective detection of distributed denial-of-service attacks,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Data mining techniques for effective detection of distributed denial-of-service attacks,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:50.040664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.668302Z digest=sha256:48567974046447fe225dc21ebf37e0e3df52fdfa48de056563367fa064a01452

Observation 160d6b52-035f-4b7e-9d48-3dc25237e82b · outbound

This paper cites An Interpretable Bearing Fault Diagnosis Model Based on Hierarchical Belief Rule Base,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data An Interpretable Bearing Fault Diagnosis Model Based on Hierarchical Belief Rule Base,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:50.026627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.672648Z digest=sha256:02cca798791d808405951e74c45880c413b3498f49885bdf48070a39c3fa0c96

Observation 835a5e8c-26c0-4963-9483-0fd27ffd02de · outbound

This paper cites Leveraging Generative Adversarial Networks for Addressing Data Imbalance in Financial Market Supervision.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Leveraging Generative Adversarial Networks for Addressing Data Imbalance in Financial Market Supervision

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-09T00:42:49.677084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:42:49.677084Z digest=sha256:acceab9b0282795c28ae293aa4168c903d19e86145f000cb49ef6a6fd0a19e34

Observation 71417e7c-021c-4c18-b7c9-305d421ab508 · outbound

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

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Few-Shot Learning with Adaptive Weight Masking in Conditional GANs,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:50.012931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.682678Z digest=sha256:de2095cf72b37636d123a1c4996ceaea882320758202eb87062c924dc49935d9

Observation 6408ed6a-642e-4349-85c5-df05d4a61e09 · outbound

This paper cites Robust Graph Neural Networks for Stability Analysis in Dynamic Networks,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Robust Graph Neural Networks for Stability Analysis in Dynamic Networks,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:49.999158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.687418Z digest=sha256:9cf40681a5386d02ae644daaf0a2d79ecfc4d8bf60f364acfc5108a2dd6da4eb

Observation 7a694a5b-b4bb-4b7c-a8cd-d65f1297c90e · outbound

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

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data The Synergistic Role of Deep Learning and Neural Architecture Search in Advancing Artificial Intelligence,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:49.984639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.692067Z digest=sha256:a34bd3c8adc332a2c910c79d48eb9dd58df4de68275ce0ac2365c62a3fbaf118

Observation 2815c5cf-ed71-47c1-b7d8-0816f35e49d8 · outbound

This paper cites Multi-Level Attention and Contrastive Learning for Enhanced Text Classification with an Optimized Transformer.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Multi-Level Attention and Contrastive Learning for Enhanced Text Classification with an Optimized Transformer

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-09T00:42:49.696908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:42:49.696908Z digest=sha256:8c4ad4cec70e9473bf64a6c03ff51e3621395ac01aacdeea177537eef0236abd

Observation e2cd91d7-5a57-46ef-a199-312e6f3431ea · outbound

This paper cites Leveraging Convolutional Neural Network-Transformer Synergy for Predictive Modeling in Risk-Based Applications.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Leveraging Convolutional Neural Network-Transformer Synergy for Predictive Modeling in Risk-Based Applications

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-09T00:42:49.838280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.701649Z digest=sha256:d9f64358dbd2a204e2222dff1a8bd75887e2eea408bc59619afc394e255ae32b

Observation 865694b1-6893-4bef-87af-8c8c6709b294 · outbound

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

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Adaptive Transaction Sequence Neural Network for Enhanced Money Laundering Detection,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:49.970433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.706709Z digest=sha256:6c94b52a54dafa56a15e12c16869d0b7fb266460893af137af0f69f89e8b8f6c

Observation 316ab3bd-33ec-42d1-bc1f-96d4d2fdb887 · outbound

This paper cites Adaptive User Interface Generation Through Reinforcement Learning: A Data-Driven Approach to Personalization and Optimization.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Adaptive User Interface Generation Through Reinforcement Learning: A Data-Driven Approach to Personalization and Optimization

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-09T00:42:49.711139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:42:49.711139Z digest=sha256:97f695037f3078a00aad618d106c4526c3d872a9bae99fd56e57e54c2e6102c4

Observation af65c484-3d92-44e0-9908-9af3ec096564 · outbound

This paper cites Self-Supervised Credit Scoring with Masked Autoencoders: Addressing Data Gaps and Noise Robustly,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Self-Supervised Credit Scoring with Masked Autoencoders: Addressing Data Gaps and Noise Robustly,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:49.955794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.715877Z digest=sha256:7884c65c78edaeb63c1855e724c4c5533942d3527a10505d88a45654bb80f407

Observation 8d48c41b-288e-4e52-8c83-0f52599a69ed · outbound

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

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-09T00:42:49.720439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:42:49.720439Z digest=sha256:2dc4b702eb764d050044151bf1990ea4ed1d43556f347cf054bb1f00f24d8807

Observation 4a1fc213-48b5-493b-9007-b921df2b5926 · outbound

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

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Calibration Learning for Few-shot Novel Product Description,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:49.940829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.725223Z digest=sha256:5043453f899896840743fac697d5822f5717f7d1e4b3b3ea5a7e9e79f9e98d6a

Observation 83edf617-9ccb-4751-830c-d45d8c41d780 · outbound

This paper cites Computer Vision-Driven Gesture Recognition: Toward Natural and Intuitive Human-Computer.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Computer Vision-Driven Gesture Recognition: Toward Natural and Intuitive Human-Computer

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-09T00:42:49.729347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:42:49.729347Z digest=sha256:8ad9e353a93c27df9acb10d86fa6c925d5ea9fdedfe49a7a1d89e0849f910324

Observation 1438720c-1b64-4171-9081-e4eeb4ead049 · outbound

This paper cites Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoders.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoders

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-09T00:42:49.733873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T00:42:49.733873Z digest=sha256:7f2a90fe41f6b9915e6d3d00c84a19d65459a4f771ddb4e03d49a91b03310a02

Observation 9514382e-619a-4843-bcd8-dd91b05cabe4 · outbound

This paper cites Comparison of Norm-Based Feature Selection Methods on Biological Omics Data,.

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data Comparison of Norm-Based Feature Selection Methods on Biological Omics Data,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T00:42:49.926399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T00:42:49.738129Z digest=sha256:de63e5815604f2e7882f7462ca0817c943f47edcc4be0e59a8ad4dc08a4c84d7

Pith citing papers

No inbound Pith citation observations are available.