Paper Citation Record · LEDGER

k-Means Clustering Is Matrix Factorization

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1512.07548.

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

pith.paper-citation-record.v1
1512.07548 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 2026-08-14T12:42:44.068196Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-24T04:48:53.876143Z

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 c513798c-6867-4a58-8929-dcfae5118be4 · inbound

Robust and Efficient Fuzzy C-Means Clustering Constrained on Flexible Sparsity cites this paper.

Robust and Efficient Fuzzy C-Means Clustering Constrained on Flexible Sparsity k-Means Clustering Is Matrix Factorization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T12:42:44.068196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6765e45a-6b25-4146-92ac-b7fb0441b5f4 · inbound

Adaptive Quantum Optimized Centroid Initialization cites this paper.

Adaptive Quantum Optimized Centroid Initialization k-Means Clustering Is Matrix Factorization

Reference 2

Resolution: malformed identifier; local_arxiv, observed 2026-05-24T04:48:53.879693Z

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.

Observation c8de1f91-150e-40d8-a007-05fe21726714 · inbound

Trusted Mamba Contrastive Network for Multi-View Clustering cites this paper.

Trusted Mamba Contrastive Network for Multi-View Clustering k-Means Clustering Is Matrix Factorization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T10:35:24.922128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75832b77-9ecf-49d8-9024-59f8e4f2936b · inbound

Forget the Data and Fine-Tuning! Just Fold the Network to Compress cites this paper.

Forget the Data and Fine-Tuning! Just Fold the Network to Compress k-Means Clustering Is Matrix Factorization

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T19:04:45.470798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf88d92c-dc57-43a4-b176-a34a2913bdae · inbound

Vocabulary-free few-shot learning for Vision-Language Models cites this paper.

Vocabulary-free few-shot learning for Vision-Language Models k-Means Clustering Is Matrix Factorization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T10:58:27.683517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.