Paper Citation Record · LEDGER

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon

As of 16 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2603.04035.

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

pith.paper-citation-record.v1
2603.04035 v4

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:00:02.110177Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

19 of 19 outbound references displayed

verified exact2
verified fuzzy0
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 81594af3-6bf1-4301-959e-584a56833940 · outbound

This paper cites TriMap: Large-scale Dimensionality Reduction Using Triplets.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon TriMap: Large-scale Dimensionality Reduction Using Triplets

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:01.861859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e7487d1-d90e-44d5-8823-b9ead316725e · outbound

This paper cites MLX : An array framework for apple silicon.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon MLX : An array framework for apple silicon

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.008650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfaec069-535f-4243-8e77-b27aee6dcbc2 · outbound

This paper cites Manifold-matching autoencoders.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Manifold-matching autoencoders

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.015074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d45b6ac5-1a63-4ef1-8d6e-0920dd014db4 · outbound

This paper cites Hamprecht, and Dmitry Kobak.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Hamprecht, and Dmitry Kobak

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.020654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4368576a-66e9-46ad-821e-92d6c809301a · outbound

This paper cites ANEgpt : Transformer training on apple neural engine.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon ANEgpt : Transformer training on apple neural engine

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.028853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0d35813-937c-4ecb-927c-0180fd11cfb8 · outbound

This paper cites Efficient k -nearest neighbor graph construction for generic similarity measures.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Efficient k -nearest neighbor graph construction for generic similarity measures

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.035043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd9bf551-9da8-4d03-abc4-de57159c410b · outbound

This paper cites DREAMS : Preserving both local and global structure in dimensionality reduction.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon DREAMS : Preserving both local and global structure in dimensionality reduction

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.040811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b52d0831-31b3-4b19-85fd-12894f801e5b · outbound

This paper cites Linderman, Manas Rachh, Jeremy G.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Linderman, Manas Rachh, Jeremy G

Reference 8

Resolution: verified exact; doi, observed 2026-08-02T19:03:28.071230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b8a27512-61be-4a4b-ab2a-42df0365bdf9 · outbound

This paper cites Training neural networks on apple neural engine.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Training neural networks on apple neural engine

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.057889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa8adb02-9e66-49af-89a0-cd4272ccc563 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.064171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dac04f1e-b6f2-4c80-9aa0-5c942168d43b · outbound

This paper cites umap-learn: UMAP -- uniform manifold approximation and projection.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon umap-learn: UMAP -- uniform manifold approximation and projection

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.070125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf61ce23-bbf2-4602-98c0-bd4ad726e47b · outbound

This paper cites Moon, David van Dijk, Zheng Wang, Scott Gigante, Daniel B.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Moon, David van Dijk, Zheng Wang, Scott Gigante, Daniel B

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.075715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d09c1336-999b-4fae-bd84-3d8cd837bd8a · outbound

This paper cites Poli c ar, Martin Stra z ar, and Bla z Zupan.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Poli c ar, Martin Stra z ar, and Bla z Zupan

Reference 13

Resolution: verified exact; doi, observed 2026-08-02T19:03:28.054429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5a4ba094-74ee-4a9c-8869-550833b75c83 · outbound

This paper cites RAPIDS cuML : Gpu machine learning algorithms.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon RAPIDS cuML : Gpu machine learning algorithms

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.086163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9a9634f-4144-4292-bdc2-0f01acd5f230 · outbound

This paper cites Visualizing data using t-SNE.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Visualizing data using t-SNE

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.091545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b93c403e-7d6b-4946-86cf-a47633a43749 · outbound

This paper cites Understanding how dimension reduction tools work: An empirical approach to deciphering t-SNE , UMAP , TriMap , and PaCMAP for data visualization.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Understanding how dimension reduction tools work: An empirical approach to deciphering t-SNE , UMAP , TriMap , and PaCMAP for data visualization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.096125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3d6fa42-5c9d-4e05-ab91-cc19e79b3b42 · outbound

This paper cites Dimension reduction with locally adjusted graphs.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Dimension reduction with locally adjusted graphs

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.100737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c891a4a0-a38f-4210-ad27-18273af089d3 · outbound

This paper cites StarMAP: Global Neighbor Embedding for Faithful Data Visualization.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon StarMAP: Global Neighbor Embedding for Faithful Data Visualization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.105375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0b362f0-6615-4c1d-9f54-e5a4585a0acd · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

mlx-vis: GPU-Native Dimensionality Reduction on Apple Silicon Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T19:00:02.110177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.