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Paper Citation Record · LEDGER

A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2206.07579.

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

pith.paper-citation-record.v1
2206.07579 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:06:14.854061Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:39:45.190281Z

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 c44f5ff6-1b0e-4ca5-8ca7-5c6d1c0c83c6 · inbound

Information-Theoretic Generative Clustering of Documents cites this paper.

Information-Theoretic Generative Clustering of Documents A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T13:06:14.854061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T13:06:14.854061Z digest=sha256:590017500e01d23bbcdf8d43ed45387f3796eb7c2fff734cf55394029a24de50

Observation ab9e2c49-ec38-42fe-a142-496e31973e33 · inbound

An Adaptive Framework for Multi-View Clustering Leveraging Conditional Entropy Optimization cites this paper.

An Adaptive Framework for Multi-View Clustering Leveraging Conditional Entropy Optimization A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T05:22:21.559999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:22:21.559999Z digest=sha256:3d709058a820572504743c4d0e17785158e651a0ae696e257934d3bc5aa76d0a

Observation 0cf03675-fe87-4919-b23d-67f21e32bacf · inbound

Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clustering cites this paper.

Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clustering A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:05:52.148222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T18:41:28.922058Z digest=sha256:1384959300c214786c595b2373a4e69e9d1682f1264f94ade82b1aa6c2abb04e

Observation 15282fc9-55df-474b-83f0-b40f17c0eadc · inbound

Cohort Organized Learning: Clustering Through Agreement cites this paper.

Cohort Organized Learning: Clustering Through Agreement A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-07-04T07:59:39.958871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T12:25:32.825189Z digest=sha256:4df47ab81f25586e7bce2be1f80297daeab543c577651b748c92f26d72148a40

Observation 69dcc22f-5421-46fa-9bdc-1db85c544099 · inbound

Bridge the Gaps: Heterogeneous Attributed Graph Clustering via Quaternion Representation Learning cites this paper.

Bridge the Gaps: Heterogeneous Attributed Graph Clustering via Quaternion Representation Learning A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:39:45.193140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T08:39:35.139965Z digest=sha256:36417fbed905f6cbf939f80ec0d9f2b56e932dba804da422a013047e99ed0d2c