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Paper Citation Record · LEDGER

HyperLogLog for probabilists

As of 7 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.22063.

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

pith.paper-citation-record.v1
2607.22063 v1

Coverage vector

measured 23 of 23 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-01T06:01:25.733455Z

measured 23 of 23 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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Reference resolution

23 of 23 outbound references displayed

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Outbound references

Observation 71b04158-26c2-46dc-a775-9d13a916573c · outbound

This paper cites The space complexity of approximating the frequency moments.

HyperLogLog for probabilists The space complexity of approximating the frequency moments

Reference 1

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source=arxiv_source observed=2026-08-01T06:01:23.247932Z digest=sha256:3e1ed5c91d8354c59610a1040e99ae066e86f393fd33d5c3e21a35e22c3d92b1

Observation 5af97921-a204-4b2d-9ebb-92df0f2cc3a5 · outbound

This paper cites Brands, F.W.

HyperLogLog for probabilists Brands, F.W

Reference 2

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source=arxiv_source observed=2026-08-01T06:01:23.375444Z digest=sha256:000de4234405c920046a13d3872f2b4c2b7599f40255f96e177e332b27837d88

Observation e5a0f2bf-c1bf-4306-9908-5e679ddf0377 · outbound

This paper cites Efficient estimation of the cardinality of large data sets.

HyperLogLog for probabilists Efficient estimation of the cardinality of large data sets

Reference 3

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source=arxiv_source observed=2026-08-01T06:01:23.509260Z digest=sha256:783dafd6a9e86a33af3d0348e8795aff76e686d994fba058de8997a5d36cecd2

Observation 67c15e0c-d772-4c06-a6b1-5855ec541fd7 · outbound

This paper cites A statistical analysis of probabilistic counting algorithms.

HyperLogLog for probabilists A statistical analysis of probabilistic counting algorithms

Reference 4

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source=arxiv_source observed=2026-08-01T06:01:23.617335Z digest=sha256:dfc74f359de6783d2fb63da0c4c9767acda4607ec8b22b21f2685d0dcee09cd6

Observation 1b3a5fc9-046b-416c-b97d-90c6aad080ee · outbound

This paper cites Loglog counting of large cardinalities.

HyperLogLog for probabilists Loglog counting of large cardinalities

Reference 5

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source=arxiv_source observed=2026-08-01T06:01:23.713220Z digest=sha256:fcb8e4580218021f94c5caccb27f6baeec9fe7592972e196a92118b81e243cde

Observation bc12168a-7981-437b-a646-b0a05a02622e · outbound

This paper cites Algorithms.

HyperLogLog for probabilists Algorithms

Reference 6

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source=arxiv_source observed=2026-08-01T06:01:23.807168Z digest=sha256:007edd07ecef6193f4d4434987bb13bc4c35dc836c5e2cc35e08ea57580fe273

Observation 0fff7be2-e0b9-4f54-b61a-cce094f42e20 · outbound

This paper cites New cardinality estimation algorithms for HyperLogLog sketches.

HyperLogLog for probabilists New cardinality estimation algorithms for HyperLogLog sketches

Reference 7

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source=arxiv_source observed=2026-08-01T06:01:23.893413Z digest=sha256:e680857811051eec64d2cae675665cc20fd788dd5b0668f8151fec9b80b0850b

Observation 6c34aac1-fe0c-4024-994a-c0509785d134 · outbound

This paper cites Counting by coin tossings.

HyperLogLog for probabilists Counting by coin tossings

Reference 8

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source=arxiv_source observed=2026-08-01T06:01:24.112482Z digest=sha256:4fab2d00b8cb629440bb5ce867d3ba4a441ad3551c26b48fb6c710bb9e693d54

Observation 21784343-39ac-43a4-b42c-a28eeef56c68 · outbound

This paper cites Probabilistic counting algorithms for data base applications.

HyperLogLog for probabilists Probabilistic counting algorithms for data base applications

Reference 9

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source=arxiv_source observed=2026-08-01T06:01:24.230322Z digest=sha256:3ef32059f6592cf86124a07699038329e99f2595b01fa6374182f723d2de03a3

Observation c466c759-e449-4962-8846-4785b7e90a9b · outbound

This paper cites Hyperloglog: the analysis of a near-optimal cardinality estimation algorithm.

HyperLogLog for probabilists Hyperloglog: the analysis of a near-optimal cardinality estimation algorithm

Reference 10

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source=arxiv_source observed=2026-08-01T06:01:24.252802Z digest=sha256:de7d761fd65720ab77179ca2e5ccb1a8e76d2a361087c13d6125b52d83dfed8e

Observation 547790fe-c611-4640-84a5-1acf50fe08cc · outbound

This paper cites Order statistics and estimating cardinalities of massive data sets.

HyperLogLog for probabilists Order statistics and estimating cardinalities of massive data sets

Reference 11

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source=arxiv_source observed=2026-08-01T06:01:24.345396Z digest=sha256:3b6a37ec9f95e567e47e3346755e63bcb9a1794569919a24cc955d04b9d18468

Observation 6478daa2-9a24-419c-a15a-dfe53a228587 · outbound

This paper cites Cardinality estimation: An experimental survey.

HyperLogLog for probabilists Cardinality estimation: An experimental survey

Reference 12

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source=arxiv_source observed=2026-08-01T06:01:24.488833Z digest=sha256:9542bbdfc92ce25407471fe00a244d88f9a1466b9d3974933e7e23af49427229

Observation d6caeb5a-0cf6-4cc3-b3c9-dc6a37d342b6 · outbound

This paper cites Hyperloglog in practice: Algorithmic engineering of a state of the art cardinality estimation algorithm.

HyperLogLog for probabilists Hyperloglog in practice: Algorithmic engineering of a state of the art cardinality estimation algorithm

Reference 13

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source=arxiv_source observed=2026-08-01T06:01:24.639336Z digest=sha256:fa316fcfd58b4613100debfbadbe06da9e1396800f772969886164a3d4456bdd

Observation 37507e14-d906-4e82-849b-32f00b63a80a · outbound

This paper cites Tight lower bounds for the distinct elements problem.

HyperLogLog for probabilists Tight lower bounds for the distinct elements problem

Reference 14

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source=arxiv_source observed=2026-08-01T06:01:24.783176Z digest=sha256:883921a4bbc0d7ca68a17e1c26c425954909a3c156047a9989aa6b861a8160ae

Observation 9dd89cc6-ca14-4493-816f-17efde6bf354 · outbound

This paper cites An optimal algorithm for the distinct elements problem.

HyperLogLog for probabilists An optimal algorithm for the distinct elements problem

Reference 15

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source=arxiv_source observed=2026-08-01T06:01:24.934012Z digest=sha256:2fa2cee19b0ff940beef52a64870241e7479ece7620c8cde47bf1f135b89195c

Observation 12491a6f-d7ae-4da5-b92a-bef00f9aee18 · outbound

This paper cites Cardinality estimation using G umbel distribution.

HyperLogLog for probabilists Cardinality estimation using G umbel distribution

Reference 16

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source=arxiv_source observed=2026-08-01T06:01:25.038787Z digest=sha256:0a98117f83ef18a039290a3ef8e6d78d2cd16c3f7c58376859a764f70d16e91b

Observation 707b9bd4-70e0-43f3-9835-2c2552d33738 · outbound

This paper cites An optimal cardinality estimation algorithm based on order statistics and its full analysis.

HyperLogLog for probabilists An optimal cardinality estimation algorithm based on order statistics and its full analysis

Reference 17

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source=arxiv_source observed=2026-08-01T06:01:25.136192Z digest=sha256:900cf34a286804c6eef79141bc57691237dcf909dd567694aa545bbd8f302190

Observation f49343e6-524f-4a66-b10b-3636d728a889 · outbound

This paper cites The Story of HyperLogLog: How Flajolet Processed Streams with Coin Flips.

HyperLogLog for probabilists The Story of HyperLogLog: How Flajolet Processed Streams with Coin Flips

Reference 18

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source=arxiv_source observed=2026-08-01T06:01:25.249834Z digest=sha256:a51861cc71dd9a7a7f0e6486d310b90d74a960b045a99a902fdf6a33dc30095d

Observation b2591ad5-f378-4952-b61b-19d02d59b634 · outbound

This paper cites Probability and computing: Randomization and probabilistic techniques in algorithms and data analysis.

HyperLogLog for probabilists Probability and computing: Randomization and probabilistic techniques in algorithms and data analysis

Reference 19

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source=arxiv_source observed=2026-08-01T06:01:25.366733Z digest=sha256:f86f6dee74d3ce81129a7f19e9aad371d524be538ee3110aad490e998ed89b42

Observation 5e2797b2-fa3b-4755-87e3-0ca5fb61dd81 · outbound

This paper cites Information theoretic limits of cardinality estimation: F isher meets S hannon.

HyperLogLog for probabilists Information theoretic limits of cardinality estimation: F isher meets S hannon

Reference 20

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source=arxiv_source observed=2026-08-01T06:01:25.462704Z digest=sha256:7c5cad6ae9ce30f963e9c205ce84ca204f4c564a6f648521cc34fa948932e8cd

Observation 6bdee1f9-4133-4b11-a4d6-14ae14d2ddd5 · outbound

This paper cites Shaked and J.G.

HyperLogLog for probabilists Shaked and J.G

Reference 21

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source=arxiv_source observed=2026-08-01T06:01:25.576499Z digest=sha256:56e890ae8c7aa83f84c1adb30d47855930b148c1e4960d55ab11636ed06d2157

Observation 594958d2-edb7-4cbd-b32d-207c007c2310 · outbound

This paper cites Big Q uery documentation: H yperloglog++ functions.

HyperLogLog for probabilists Big Q uery documentation: H yperloglog++ functions

Reference 22

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source=arxiv_source observed=2026-08-01T06:01:25.651702Z digest=sha256:ba061c5b0ea5183c7a3273b78c8b03bd8174c195f9d94d608997e1323f5a5517

Observation e93e58fd-76ff-4d5c-95a2-0898ea8b16f1 · outbound

This paper cites Redis documentation: H yperloglog.

HyperLogLog for probabilists Redis documentation: H yperloglog

Reference 23

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source=arxiv_source observed=2026-08-01T06:01:25.733455Z digest=sha256:6dcdccd05ee40739bdae342d7d9d3ad7e5b331af104d2cb40eb2494d63d3314d

Pith citing papers

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