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Paper Citation Record · LEDGER

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM

As of 9 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.28635.

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

pith.paper-citation-record.v1
2607.28635 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T00:55:00.014770Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

31 of 31 outbound references displayed

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  • unresolved31
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  • malformed identifier0
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External citation measurements

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Outbound references

Observation 52aa1218-5ed7-4113-9530-823ecbd223e6 · outbound

This paper cites Biometrics 49(3), 803–821 (1993).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Biometrics 49(3), 803–821 (1993)

Reference 1

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Observation f7cfedf7-b1bd-427a-9535-db6968280a39 · outbound

This paper cites ACM Computing Surveys55(7), 1–39 (2022).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM ACM Computing Surveys55(7), 1–39 (2022)

Reference 2

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Observation 9d2602d3-d582-431a-b50d-1139a20ec17d · outbound

This paper cites In: ICDMW.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM In: ICDMW

Reference 3

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Observation a7b0a706-2ac0-480e-830d-0ad76eca9f7e · outbound

This paper cites an unresolved cited work.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Unresolved cited work

Reference 4

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Observation 97ed883f-76b4-4dca-afb0-6f224087017b · outbound

This paper cites Journal of the Royal Statistical Society: Series B39(1), 1–22.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Journal of the Royal Statistical Society: Series B39(1), 1–22

Reference 5

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Observation edc047f7-3077-4d01-88be-c35f419f3392 · outbound

This paper cites Advances in neural information processing sys- tems27(2014).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Advances in neural information processing sys- tems27(2014)

Reference 6

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Observation 822e2a42-eac2-4edd-afbf-7d4e21fbca9f · outbound

This paper cites Pattern Recognition36(2), 463–473 (2003).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Pattern Recognition36(2), 463–473 (2003)

Reference 7

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Observation 6fe27d16-eaec-4699-9e4c-8e6996410620 · outbound

This paper cites John Wiley & Sons (2013).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM John Wiley & Sons (2013)

Reference 8

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Observation 9f081e26-edb9-41d4-91cf-7112d8bd80f4 · outbound

This paper cites an unresolved cited work.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Unresolved cited work

Reference 9

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Observation 959e4d42-36d0-4250-bf97-6c21a0efeffc · outbound

This paper cites Frontiers in Applied Mathematics and Statistics5(2020).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Frontiers in Applied Mathematics and Statistics5(2020)

Reference 10

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Observation 0ced5d60-e6b0-48f6-8d90-113ef763575c · outbound

This paper cites Advances in Data Analysis and Classification pp.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Advances in Data Analysis and Classification pp

Reference 11

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Observation b4347872-1e7a-41fe-9c68-0a142f430bad · outbound

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Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Unresolved cited work

Reference 12

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Observation 3fea4915-d63b-45b8-80fc-c7b59927ce71 · outbound

This paper cites an unresolved cited work.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Unresolved cited work

Reference 13

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This paper cites an unresolved cited work.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Unresolved cited work

Reference 14

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Observation 64cc2025-7797-491d-99f7-324fdf6d0af7 · outbound

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Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Unresolved cited work

Reference 15

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Observation ffaf0515-16ba-4fe4-ad36-a03d13a2ca01 · outbound

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Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Unresolved cited work

Reference 16

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Observation 12037c01-33e9-4263-ba58-f7b2d4e2cb6f · outbound

This paper cites In: Vlachos, A., Augenstein, I.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM In: Vlachos, A., Augenstein, I

Reference 17

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Observation 463afceb-7fa2-4bb1-8eea-100b66dbb5a3 · outbound

This paper cites In: Inter- national Symposium on Intelligent Data Analysis.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM In: Inter- national Symposium on Intelligent Data Analysis

Reference 18

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Observation 597aa2e2-c3c2-4ee1-ab15-d221a2b28e64 · outbound

This paper cites In: Companion proceedings of the web conference 2020.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM In: Companion proceedings of the web conference 2020

Reference 19

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Observation 67e7d95f-23e7-41f7-9a9e-48b6fd7a2ec3 · outbound

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Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Khalal et al

Reference 20

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Observation aceadec7-ca97-468b-bdef-fc803749ce05 · outbound

This paper cites In: Pro- ceedings of the 2017 SIAM International Conference on Data Mining.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM In: Pro- ceedings of the 2017 SIAM International Conference on Data Mining

Reference 21

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Observation 204a63b3-85cd-462a-bbb4-7efb7de013eb · outbound

This paper cites Data Mining and Knowledge Discovery31, 1218–1241 (2017).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Data Mining and Knowledge Discovery31, 1218–1241 (2017)

Reference 22

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Observation d57260b0-ca1f-4857-b335-862c89f9a403 · outbound

This paper cites Advances in Data Analysis and Classification 13, 591–620 (2019).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Advances in Data Analysis and Classification 13, 591–620 (2019)

Reference 23

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Observation 18e78c96-db90-4b2f-a913-d1b796254406 · outbound

This paper cites Nature631(8022), 755–759 (Jul 2024).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Nature631(8022), 755–759 (Jul 2024)

Reference 24

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Observation b574d350-4e38-43e6-a73a-9dbc1a7e3e4d · outbound

This paper cites Psychological methods9(3), 386 (2004).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Psychological methods9(3), 386 (2004)

Reference 25

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Observation b14528f5-c82d-472f-9d3c-fcdd8e69ced1 · outbound

This paper cites Journal of machine learning research3(Dec), 583–617 (2002).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Journal of machine learning research3(Dec), 583–617 (2002)

Reference 26

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Observation 38d1fdf2-507f-47ae-8ec1-faf19d76303a · outbound

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Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Halsted Press book

Reference 27

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This paper cites In: the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM In: the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis

Reference 28

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Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Unresolved cited work

Reference 29

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Observation f1bdf595-74b4-4236-a3d4-d27c09f3ee97 · outbound

This paper cites Journal of the American Statistical Association77(380), 841–847 (1982).

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM Journal of the American Statistical Association77(380), 841–847 (1982)

Reference 30

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Observation 5922a9a9-8648-4cf7-b116-e7b7d874fc53 · outbound

This paper cites LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition.

Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition

Reference 31

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Pith citing papers

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