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Paper Citation Record · LEDGER

Parallel Hierarchical Agglomerative Clustering in Low Dimensions

As of 11 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2507.20047.

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

pith.paper-citation-record.v1
2507.20047 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:12:39.200727Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

39 of 39 outbound references displayed

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  • verified fuzzy32
  • unresolved5
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b67b0f59-327c-4f10-bc6a-8e01934605c6 · outbound

This paper cites Subquadratic high-dimensional hierarchical clustering.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Subquadratic high-dimensional hierarchical clustering

Reference 1

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Observation 7ed46717-7258-423a-b6ff-a5c59b9dfcff · outbound

This paper cites Efficient centroid-linkage clustering.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Efficient centroid-linkage clustering

Reference 2

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Observation f3388ba0-6126-453b-981c-9df911f23d3e · outbound

This paper cites It's hard to hac with average linkage! In International Colloquium on Automata, Languages and Programming (ICALP) , 2024.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions It's hard to hac with average linkage! In International Colloquium on Automata, Languages and Programming (ICALP) , 2024

Reference 3

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Observation 097fcefe-66c2-44c4-8bfd-1e4ea2c3603b · outbound

This paper cites Introduction to Parallel Algorithms (DRAFT) , 2024.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Introduction to Parallel Algorithms (DRAFT) , 2024

Reference 4

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Source-reported events for the cited work

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Observation 7adf259f-4189-4927-a847-ec36e57521a8 · outbound

This paper cites Cover trees for nearest neighbor.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Cover trees for nearest neighbor

Reference 5

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Source-reported events for the cited work

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Observation 1799635d-f62a-462e-8b38-775d7629d40c · outbound

This paper cites The complexity of the comparator circuit value problem.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions The complexity of the comparator circuit value problem

Reference 6

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Observation 9b96c325-1719-47f9-b779-19928bc81c3b · outbound

This paper cites Twister tries: Approximate hierarchical agglomerative clustering for average distance in linear time.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Twister tries: Approximate hierarchical agglomerative clustering for average distance in linear time

Reference 7

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Source-reported events for the cited work

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Observation 0ffcccb9-366f-49ce-8268-1b53008b2ea0 · outbound

This paper cites Optimal parallel algorithms for dendrogram computation and single-linkage clustering.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Optimal parallel algorithms for dendrogram computation and single-linkage clustering

Reference 8

Resolution
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Source-reported events for the cited work

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Observation 5d117c95-ccbe-4f42-9b30-f2568ff1de18 · outbound

This paper cites Hierarchical agglomerative graph clustering in nearly-linear time.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Hierarchical agglomerative graph clustering in nearly-linear time

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation e36b9724-db05-47fe-b39f-5574a76c8cfd · outbound

This paper cites Hierarchical agglomerative graph clustering in poly-logarithmic depth.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Hierarchical agglomerative graph clustering in poly-logarithmic depth

Reference 10

Resolution
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Source-reported events for the cited work

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Observation bf0e1fce-4a62-49fe-b1b2-c9e160f06db3 · outbound

This paper cites The Faiss library.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions The Faiss library

Reference 11

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Observation f5a9a21f-98b0-4ca8-8d68-d93c00f19198 · outbound

This paper cites Terahac: Hierarchical agglomerative clustering of trillion-edge graphs.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Terahac: Hierarchical agglomerative clustering of trillion-edge graphs

Reference 12

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Source-reported events for the cited work

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Observation f3971baf-ac83-453f-b77f-70d339e4cf4b · outbound

This paper cites ParlayANN: Scalable and Deterministic Parallel Graph-Based Approximate Nearest Neighbor Search Algorithms.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions ParlayANN: Scalable and Deterministic Parallel Graph-Based Approximate Nearest Neighbor Search Algorithms

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d84fba27-5b3a-4d98-879b-feed841a0710 · outbound

This paper cites A new near-linear time algorithm for k-nearest neighbor search using a compressed cover tree.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions A new near-linear time algorithm for k-nearest neighbor search using a compressed cover tree

Reference 14

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Source-reported events for the cited work

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Observation fe5169a4-02b2-4383-9643-8b40197acd0d · outbound

This paper cites Clustering for private interest-based advertising.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Clustering for private interest-based advertising

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 3807f092-d207-45d9-974d-c9048ad18057 · outbound

This paper cites Tight analysis of parallel randomized greedy mis.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Tight analysis of parallel randomized greedy mis

Reference 16

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Source-reported events for the cited work

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Observation 7246d57b-73b1-4bf2-b9e9-fb7948535af4 · outbound

This paper cites Parallel cover trees and their applications.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Parallel cover trees and their applications

Reference 17

Resolution
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Source-reported events for the cited work

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Observation f57116fb-c118-4f5e-95df-7dda1a2b8d75 · outbound

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Parallel Hierarchical Agglomerative Clustering in Low Dimensions Unresolved cited work

Reference 18

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Source-reported events for the cited work

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Observation 84587bce-55b6-401d-887d-a75b84f2eb79 · outbound

This paper cites Analysis of ward's method.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Analysis of ward's method

Reference 19

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Source-reported events for the cited work

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Observation db01629a-9847-498d-9be4-bd6130b69b0c · outbound

This paper cites Clustering.jl.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Clustering.jl

Reference 20

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Source-reported events for the cited work

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Observation 1185c031-5934-450c-b4d1-4281bff528c1 · outbound

This paper cites Hierarchical clustering.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Hierarchical clustering

Reference 21

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Source-reported events for the cited work

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Observation 7d5a4602-cad9-4c89-a186-847976edf184 · outbound

This paper cites A framework for parallelizing hierarchical clustering methods.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions A framework for parallelizing hierarchical clustering methods

Reference 22

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Source-reported events for the cited work

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Observation 84750ca7-8280-4217-b1fb-46efa0873442 · outbound

This paper cites A general theory of classificatory sorting strategies: 1.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions A general theory of classificatory sorting strategies: 1

Reference 23

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Source-reported events for the cited work

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Observation c0228cc6-434b-4fd7-9050-287bd095b2b8 · outbound

This paper cites Agglomerative hierarchical cluster tree - matlab linkage.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Agglomerative hierarchical cluster tree - matlab linkage

Reference 24

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Source-reported events for the cited work

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Observation e5d2d0bd-db47-4b21-8367-0fd96362b4e1 · outbound

This paper cites Algorithms for hierarchical clustering: an overview.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Algorithms for hierarchical clustering: an overview

Reference 25

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Source-reported events for the cited work

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Observation 66f98fbf-e0be-4fef-bb75-0b9fce736ff8 · outbound

This paper cites Algorithms for hierarchical clustering: an overview, ii.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Algorithms for hierarchical clustering: an overview, ii

Reference 26

Resolution
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Source-reported events for the cited work

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Observation bd07af3e-be55-41ed-a745-969d2d96789a · outbound

This paper cites The complexity of circuit value and network stability.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions The complexity of circuit value and network stability

Reference 27

Resolution
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Source-reported events for the cited work

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Observation 6ea9d626-1bfa-47e3-b596-54d4a4bf80be · outbound

This paper cites fastcluster: Fast hierarchical, agglomerative clustering routines for r and python.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions fastcluster: Fast hierarchical, agglomerative clustering routines for r and python

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Parallel Hierarchical Agglomerative Clustering in Low Dimensions Unresolved cited work

Reference 29

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Source-reported events for the cited work

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Observation ab358831-d0cf-40ec-8463-81df57983690 · outbound

This paper cites Scikit-learn: Machine learning in python.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Scikit-learn: Machine learning in python

Reference 30

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d433fda8-832d-436a-acbe-417da1b89d35 · outbound

This paper cites hclust function - rdocumentation.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions hclust function - rdocumentation

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8374ca81-97f5-4c47-9e7c-361f97ec8bc2 · outbound

This paper cites Parallel algorithm and complexity results for telephone link simulation.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Parallel algorithm and complexity results for telephone link simulation

Reference 32

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verified fuzzy
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Source-reported events for the cited work

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Observation bd8a0f83-0883-43e3-8709-3f1985b7a827 · outbound

This paper cites Diskann: Fast accurate billion-point nearest neighbor search on a single node.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Diskann: Fast accurate billion-point nearest neighbor search on a single node

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 0edd9991-bed1-4081-8fff-9589224a42c0 · outbound

This paper cites A new approach to stable matching problems.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions A new approach to stable matching problems

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation b0700936-92bd-4c20-99e2-0c5d4cb5aa85 · outbound

This paper cites How small is a unit ball? Mathematics Magazine , 62(2):101--107, 1989.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions How small is a unit ball? Mathematics Magazine , 62(2):101--107, 1989

Reference 35

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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 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-06T14:12:39.182107Z digest=sha256:dcfe3cf10a45581d09383359a10e626ce1b0cd01e220d0afb1db6baa528c368e

Observation 2e078d8c-809b-4c5a-ba14-f91157844421 · outbound

This paper cites Alglib, a simple symbol-manipulation package.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Alglib, a simple symbol-manipulation package

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:12:39.331198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-06T14:12:39.186181Z digest=sha256:094bf228a0673ceaf9701e91af8198a16994e5b0c0844cc8f32a2973f65c5700

Observation 53edb0aa-a794-41d0-a1f1-bd61920a8b50 · outbound

This paper cites Scipy 1.0: fundamental algorithms for scientific computing in python.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions Scipy 1.0: fundamental algorithms for scientific computing in python

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:12:39.314926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-06T14:12:39.191876Z digest=sha256:7b57df517a4e60dd935acbe676b52d3068ccf5cb18960fe5d62a82e139a37954

Observation b6e99f58-8ff8-49c1-bfb1-0369c5866d4e · outbound

This paper cites DynHAC: Fully Dynamic Approximate Hierarchical Agglomerative Clustering.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions DynHAC: Fully Dynamic Approximate Hierarchical Agglomerative Clustering

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:12:39.266760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-06T14:12:39.196340Z digest=sha256:eba906bfd0cc61e930b96da276a4644aacae3020d2520a40e7a37fc655099613

Observation f0750a31-e132-4889-ba82-eb514e26e711 · outbound

This paper cites The ParClusterers Benchmark Suite (PCBS): A Fine-Grained Analysis of Scalable Graph Clustering.

Parallel Hierarchical Agglomerative Clustering in Low Dimensions The ParClusterers Benchmark Suite (PCBS): A Fine-Grained Analysis of Scalable Graph Clustering

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:12:39.243777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-06T14:12:39.200727Z digest=sha256:171e4376568983a35fe99b622c07c9883cdbdacc57100d976a7724e51819693f

Pith citing papers

No inbound Pith citation observations are available.