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Paper Citation Record · LEDGER

Approximate Borderline Sampling using Granular-Ball for Classification Tasks

As of 19 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2506.02366.

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

pith.paper-citation-record.v1
2506.02366 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:30:34.946094Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

47 of 47 outbound references displayed

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  • verified fuzzy28
  • unresolved18
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ea7eda7b-a542-4a07-a217-fff68a0e5d50 · outbound

This paper cites Adversarial robustness of streaming algorithms through impor- tance sampling,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Adversarial robustness of streaming algorithms through impor- tance sampling,

Reference 1

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Observation e1eb5be9-762b-4709-a26c-dbe4987758e5 · outbound

This paper cites Distilling effective supervision from severe label noise,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Distilling effective supervision from severe label noise,

Reference 2

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Source-reported events for the cited work

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Observation 8a77755b-72d4-42b0-a094-1d2da15a2d6e · outbound

This paper cites A Comparison of Synthetic Oversampling Methods for Multi-class Text Classification.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks A Comparison of Synthetic Oversampling Methods for Multi-class Text Classification

Reference 3

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Observation d07cf0c9-9d45-4910-8d83-81b47e639072 · outbound

This paper cites Coreset sampling from open-set for fine-grained self-supervised learning,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Coreset sampling from open-set for fine-grained self-supervised learning,

Reference 4

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Source-reported events for the cited work

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Observation df730c2a-b0c3-48da-9194-7c0137a2a37e · outbound

This paper cites Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 2e35610a-48e5-47ab-8ac8-bc3084235afc · outbound

This paper cites Attention-based point cloud edge sampling,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Attention-based point cloud edge sampling,

Reference 6

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Source-reported events for the cited work

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Observation bf6a37d3-8d93-4b24-8718-48335111518a · outbound

This paper cites Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fbcc252b-f6e2-4055-b99e-da9c7aebdc47 · outbound

This paper cites Unsupervised sampling promoting for stochastic human trajectory prediction,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Unsupervised sampling promoting for stochastic human trajectory prediction,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 4378cc85-ca16-4879-b7d8-e781e251d436 · outbound

This paper cites Model-based synthetic sampling for imbal- anced data,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Model-based synthetic sampling for imbal- anced data,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f60bc015-1350-4f4e-ad19-049f80541702 · outbound

This paper cites A robust oversampling approach for class imbalance problem with small disjuncts,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks A robust oversampling approach for class imbalance problem with small disjuncts,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3ada6b1c-230a-443f-a84a-64d5f31c334d · outbound

This paper cites A review of methods for imbalanced multi-label classification,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks A review of methods for imbalanced multi-label classification,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ee9953fc-761d-43ac-a451-62bc8e8c76eb · outbound

This paper cites Borderline-smote: a new over- sampling method in imbalanced data sets learning,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Borderline-smote: a new over- sampling method in imbalanced data sets learning,

Reference 12

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Source-reported events for the cited work

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Observation 14d9f1c0-e71c-41f8-8062-8fe23feff423 · outbound

This paper cites Deepsmote: Fusing deep learning and smote for imbalanced data,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Deepsmote: Fusing deep learning and smote for imbalanced data,

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6a94290d-57d5-4467-95b1-7302579dc07b · outbound

This paper cites Adasyn- random forest based intrusion detection model,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Adasyn- random forest based intrusion detection model,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ec1c1d77-cf84-4246-a558-117b3521f48a · outbound

This paper cites Abnormal samples oversampling for anomaly detection based on uniform scale strategy and closed area,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Abnormal samples oversampling for anomaly detection based on uniform scale strategy and closed area,

Reference 15

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 70aa08ec-84c1-4fb0-b595-82a704443d37 · outbound

This paper cites Two modifications of cnn,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Two modifications of cnn,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 712cc73b-8794-4b07-b6c5-a061cc75e9b5 · outbound

This paper cites Random sampling with a reservoir,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Random sampling with a reservoir,

Reference 17

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Source-reported events for the cited work

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Observation 3bc97d92-dbb4-487b-a99a-5fcd60ceb27e · outbound

This paper cites an unresolved cited work.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Unresolved cited work

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 928186d4-b436-4c97-b7dc-8335f4899d32 · outbound

This paper cites an unresolved cited work.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Unresolved cited work

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 985b283f-690c-4099-91b1-bce68a55b184 · outbound

This paper cites Random forests,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Random forests,

Reference 20

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Source-reported events for the cited work

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Observation b705bb23-381a-407f-8956-134855788fc0 · outbound

This paper cites Fuzzy sets and information granularity,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Fuzzy sets and information granularity,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ee39f389-ef40-4f07-bb40-f819f60a97d8 · outbound

This paper cites Granular ball computing classifiers for efficient, scalable and robust learning,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Granular ball computing classifiers for efficient, scalable and robust learning,

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ea0b1d45-3623-4eb3-b86a-fa434d6c0cff · outbound

This paper cites Granular ball sampling for noisy label classification or imbalanced classification,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Granular ball sampling for noisy label classification or imbalanced classification,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9ba2588f-6f4a-40d0-b362-3e3ddba15ab0 · outbound

This paper cites k-times markov sampling for svmc,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks k-times markov sampling for svmc,

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 66deeb00-58e6-4420-bd8d-afbea38760f6 · outbound

This paper cites Reduction of training data for support vector machine: a survey,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Reduction of training data for support vector machine: a survey,

Reference 25

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 99462150-c753-4533-b70b-d56f2cfd5dd7 · outbound

This paper cites A method to improve support vector machine based on distance to hyperplane,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks A method to improve support vector machine based on distance to hyperplane,

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f5bf6bcc-421f-442e-991d-81a3cf6f5657 · outbound

This paper cites An efficient and adaptive granular-ball generation method in classification problem,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks An efficient and adaptive granular-ball generation method in classification problem,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 758cffb9-1064-4ff0-ad8b-c62f03a5c3a3 · outbound

This paper cites 3wc- gbnrs++: A novel three-way classifier with granular-ball neighborhood rough sets based on uncertainty,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks 3wc- gbnrs++: A novel three-way classifier with granular-ball neighborhood rough sets based on uncertainty,

Reference 28

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Source-reported events for the cited work

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Observation 67932a58-e72f-48c0-8077-8ed8c75d5698 · outbound

This paper cites A fast granular-ball-based density peaks clustering algorithm for large-scale data,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks A fast granular-ball-based density peaks clustering algorithm for large-scale data,

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d3e5727e-e315-4470-8594-a84a89da1485 · outbound

This paper cites An efficient spectral clustering algorithm based on granular-ball,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks An efficient spectral clustering algorithm based on granular-ball,

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ab477aa0-bc3c-4add-9ae8-dca3a619d132 · outbound

This paper cites W-gbc: An adaptive weighted clustering method based on granular-ball structure,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks W-gbc: An adaptive weighted clustering method based on granular-ball structure,

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 7982ab4b-4272-457f-9d51-2c8abb58e3fb · outbound

This paper cites Granular-ball fuzzy set and its implement in svm,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Granular-ball fuzzy set and its implement in svm,

Reference 32

Resolution
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Source-reported events for the cited work

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Observation 59ea1f43-1c14-4830-8fae-467c1caf4afc · outbound

This paper cites Incremental learning based on granular ball rough sets for classifica- tion in dynamic mixed-type decision system,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Incremental learning based on granular ball rough sets for classifica- tion in dynamic mixed-type decision system,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:30:35.184538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 27a365d7-89d0-426f-9bd4-12a90159e307 · outbound

This paper cites Open continual feature selection via granular-ball knowledge transfer,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Open continual feature selection via granular-ball knowledge transfer,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:30:35.171544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a349d63a-240e-4418-8c2a-29c6a6a6aacc · outbound

This paper cites Gbnrs: A novel rough set algorithm for fast adaptive attribute reduction in classification,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Gbnrs: A novel rough set algorithm for fast adaptive attribute reduction in classification,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:30:35.158270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8d7a0a11-c271-4592-a046-964562369f7f · outbound

This paper cites Grrs: Accurate and efficient neighborhood rough set for feature selection,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Grrs: Accurate and efficient neighborhood rough set for feature selection,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:30:35.145181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9198eef9-276d-46a5-83f6-a29ecf30ce8c · outbound

This paper cites Graph-based Representation for Image based on Granular-ball.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Graph-based Representation for Image based on Granular-ball

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:30:34.988301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 89ad8326-17f6-4773-8a7b-1bd6bf2079a8 · outbound

This paper cites Gbg++: A fast and stable granular ball generation method for clas- sification,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Gbg++: A fast and stable granular ball generation method for clas- sification,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T11:30:34.912437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0639534b-e43f-4272-bf20-d307e9f62e67 · outbound

This paper cites Smote: synthetic minority over-sampling technique,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Smote: synthetic minority over-sampling technique,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T11:30:34.916239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:30:34.916239Z digest=sha256:4c5ef11fe32e96661ed404f8e84c1341ee91aca52dc16c6c242196073001318f

Observation 597bf2cf-b3dd-4356-92eb-86258abf06b1 · outbound

This paper cites Nearest neighbor pattern classification,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Nearest neighbor pattern classification,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T11:30:34.920045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:30:34.920045Z digest=sha256:2e8adf6649e13ee786d1f73454abcd4fb4a725447b3778b6a41d94ae20b2e0e3

Observation d4b4cc68-ae85-44a5-95ad-8e900006cda9 · outbound

This paper cites Clas- sification and regression trees,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Clas- sification and regression trees,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:30:35.103690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T11:30:34.923931Z digest=sha256:4dd96896123dff3a08195f1e9f825a56599eef6c31de4a328e45e521f18d4678

Observation e1cbfc4c-16fa-462b-904a-95022bc3f5db · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Lightgbm: A highly efficient gradient boosting decision tree,

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T11:30:34.927572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:30:34.927572Z digest=sha256:642e739e19cc8b605a896c48b2073200c2e9171c32430716927f8782aa9f5598

Observation e63dd8eb-2b48-4c40-800a-938ce10f5cbf · outbound

This paper cites Xgboost: A scalable tree boosting system,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Xgboost: A scalable tree boosting system,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T11:30:34.931118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:30:34.931118Z digest=sha256:1790e3de0fe5c9fbc066bec6fa3292040882bff646aa3592526338e46d4fc009

Observation 9bddce1a-9c50-4378-bcfe-c9e7e63b9fa9 · outbound

This paper cites an unresolved cited work.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:30:35.073092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 01bc80e4-ae5f-43c3-8e76-06462b407669 · outbound

This paper cites Keel data-mining software tool: Data set repository, integration of algorithms and experi- mental analysis framework,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Keel data-mining software tool: Data set repository, integration of algorithms and experi- mental analysis framework,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:30:35.059337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T11:30:34.938693Z digest=sha256:a4fad114c2caef4494a088de5475167aeea0b2486e8a55c8363b17b5018415c5

Observation 5bb6a5f5-287b-4169-a4b1-95ec73783706 · outbound

This paper cites The use of machine learning methods in classification of pumpkin seeds (cucurbita pepo l.),.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks The use of machine learning methods in classification of pumpkin seeds (cucurbita pepo l.),

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:30:35.045779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0c972fdd-29d8-45a4-86f7-89490ef2ebc4 · outbound

This paper cites Speed up kernel discriminant analysis,.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks Speed up kernel discriminant analysis,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:30:35.031977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T11:30:34.946094Z digest=sha256:fb73988bdb332ab96593ddf50474b61ca7d365814e0183c1a22349412b47ec5c

Pith citing papers

No inbound Pith citation observations are available.