Paper Citation Record · LEDGER

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines

As of 7 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2607.25356.

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

pith.paper-citation-record.v1
2607.25356 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T02:42:55.545446Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

34 of 34 outbound references displayed

verified exact4
verified fuzzy0
unresolved29
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ebcf8ea9-d0fa-43ea-b1ae-0e220f4c76ec · outbound

This paper cites an unresolved cited work.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Unresolved cited work

Reference 1

Resolution: malformed identifier; no resolver link, observed 2026-08-01T02:42:55.470456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c17146a0-6516-4d8b-8229-561d86ce0e45 · outbound

This paper cites VLDB Journal24(4), 557–581 (2015).https://doi.org/10.1007/s00778-015-0389-y.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines VLDB Journal24(4), 557–581 (2015).https://doi.org/10.1007/s00778-015-0389-y

Reference 2

Resolution: verified exact; doi, observed 2026-08-01T02:46:04.029012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 83f63ccb-c613-4ad8-8d36-e9e469b282f3 · outbound

This paper cites In: EuroSys.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines In: EuroSys

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.476110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c03a6bbf-19ad-4355-b89e-9ad01523890f · outbound

This paper cites Knowledge and Information Systems11(2), 191–215 (2007).https: //doi.org/10.1007/s10115-006-0006-x.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Knowledge and Information Systems11(2), 191–215 (2007).https: //doi.org/10.1007/s10115-006-0006-x

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.478813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa72373f-dc03-4200-a67b-ba9c642ad95b · outbound

This paper cites In: 34th IEEE International Conference on Data Engineering (ICDE).

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines In: 34th IEEE International Conference on Data Engineering (ICDE)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.481306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 344e2ecd-7b8f-4cae-8012-f6db23f8f6f4 · outbound

This paper cites International Journal of In- formation Quality2(4), 300–323 (2011).https://doi.org/10.1504/IJIQ.2011.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines International Journal of In- formation Quality2(4), 300–323 (2011).https://doi.org/10.1504/IJIQ.2011

Reference 6

Resolution: verified exact; doi, observed 2026-08-01T02:46:03.681120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d0ca955f-ace3-49d1-8bc4-31e429cb149f · outbound

This paper cites Proceedings of the VLDB Endowment (PVLDB)11(8), 880–892 (2018).

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Proceedings of the VLDB Endowment (PVLDB)11(8), 880–892 (2018)

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.486438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e517e830-bdc9-496e-96ce-a89bcbc70208 · outbound

This paper cites Accounting for Variance in Machine Learning Benchmarks.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Accounting for Variance in Machine Learning Benchmarks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.488694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f48967d9-32d6-4535-8501-a730fffb12c6 · outbound

This paper cites Nature Reviews Neuroscience14(5), 365–376 (2013).

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Nature Reviews Neuroscience14(5), 365–376 (2013)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.491775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7304a623-dd3f-4b63-8dfc-350e558ffa9c · outbound

This paper cites Foundations and Trends in Databases 4(1–3), 1–294 (2011).https://doi.org/10.1561/1900000004.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Foundations and Trends in Databases 4(1–3), 1–294 (2011).https://doi.org/10.1561/1900000004

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.494039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 616253c6-1124-42c7-a9f5-5b1ee152aad5 · outbound

This paper cites In: Information Processing Letters.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines In: Information Processing Letters

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.496138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22f90487-d2ed-4079-a0f0-339e88ebb8cf · outbound

This paper cites VLDB Journal31, 1103–1126 (2022).https://doi.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines VLDB Journal31, 1103–1126 (2022).https://doi

Reference 12

Resolution: verified exact; doi, observed 2026-08-01T02:46:03.491825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9de3d662-3e63-4a01-b471-3d36155eb2e0 · outbound

This paper cites In: SIGMOD.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines In: SIGMOD

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.500688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23998afe-7723-4499-9762-3c1692219000 · outbound

This paper cites an unresolved cited work.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.502740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b70c7965-e576-4636-abdb-78949eed0131 · outbound

This paper cites In: SIGMOD.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines In: SIGMOD

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.504654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c259018a-c011-4471-a5f6-e66f24f2c647 · outbound

This paper cites Journal of the American Statistical Association47(260), 663–685 (1952).https://doi.org/10.1080/01621459.1952.10483446.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Journal of the American Statistical Association47(260), 663–685 (1952).https://doi.org/10.1080/01621459.1952.10483446

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.506647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b78ad454-5b88-4ced-b5b8-9f57123e089f · outbound

This paper cites an unresolved cited work.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.508852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ae5962c-4399-42da-8b6b-ced77e611ff5 · outbound

This paper cites an unresolved cited work.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.510797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6be7504d-fa09-4b81-9a2f-b2d725cef06f · outbound

This paper cites DataPerf: Benchmarks for Data-Centric AI Development.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines DataPerf: Benchmarks for Data-Centric AI Development

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.512734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d52715c0-f1fe-4d4e-82ef-d57525bacc00 · outbound

This paper cites Morgan & Claypool Publishers (2010).https://doi.org/10.1007/978-3-031-01835-0.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Morgan & Claypool Publishers (2010).https://doi.org/10.1007/978-3-031-01835-0

Reference 20

Resolution: verified exact; doi, observed 2026-08-01T02:46:03.226285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a6aa741d-b325-458b-a467-a92d7017bb8d · outbound

This paper cites Journal of the Royal Statistical Society97(4), 558–625 (1934).https://doi.org/10.2307/2342192.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Journal of the Royal Statistical Society97(4), 558–625 (1934).https://doi.org/10.2307/2342192

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.518591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17a5d66c-72bb-4eca-8874-35bab721fc14 · outbound

This paper cites In: SIGMOD.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines In: SIGMOD

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.520841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf2229eb-6755-450d-bfbc-89e3d5fd8d59 · outbound

This paper cites an unresolved cited work.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.522945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49f3fcce-e2c3-4bdb-b482-8d9f255d6ae3 · outbound

This paper cites an unresolved cited work.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.524999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 771ace62-ed4b-47af-8ee9-0a9d22f66ffd · outbound

This paper cites PVLDB1(1), 797–808 (2008).https://doi.org/10.14778/1453856.1453943.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines PVLDB1(1), 797–808 (2008).https://doi.org/10.14778/1453856.1453943

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.526963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 048dee47-3ab7-4735-b10e-69ae6344ebac · outbound

This paper cites In: VLDB.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines In: VLDB

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.529009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd6789c2-00ac-4739-a935-1c46519e2a5d · outbound

This paper cites Proceedings of the VLDB Endow- ment (PVLDB)11(12), 1781–1794 (2018).https://doi.org/10.14778/3229863.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Proceedings of the VLDB Endow- ment (PVLDB)11(12), 1781–1794 (2018).https://doi.org/10.14778/3229863

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.530907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d4cf2e7-c499-4e92-8bd3-5e0cc1ee95c9 · outbound

This paper cites Journal of the American Statisti- cal Association85(412), 1050–1059 (1990).https://doi.org/10.1080/01621459.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Journal of the American Statisti- cal Association85(412), 1050–1059 (1990).https://doi.org/10.1080/01621459

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.533180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8aabb816-416f-44b9-bd1f-98dbe7cc6c04 · outbound

This paper cites In: Proc.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines In: Proc

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.535545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11dded96-7b88-48f3-85de-9b04de29b61e · outbound

This paper cites ACM Transactions on Mathemat- ical Software11(1), 37–57 (1985).https://doi.org/10.1145/3147.3165 Data Quality Profiling at Scale with Progressive Sampling 29.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines ACM Transactions on Mathemat- ical Software11(1), 37–57 (1985).https://doi.org/10.1145/3147.3165 Data Quality Profiling at Scale with Progressive Sampling 29

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.537447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44c7d0b8-aec7-432c-b74c-19cc00a81ad4 · outbound

This paper cites VLDB Journal32(4), 791–813 (2023).https://doi.org/10.1007/s00778-022-00775-9.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines VLDB Journal32(4), 791–813 (2023).https://doi.org/10.1007/s00778-022-00775-9

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.539381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07b60f94-8b27-44d5-b6a3-795b533c2b8f · outbound

This paper cites Harper and Row, New York, 2nd edn.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines Harper and Row, New York, 2nd edn

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.541489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dddac27-d984-4c77-9667-b44882ac0886 · outbound

This paper cites ACM Computing Surveys57(5) (2025).

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines ACM Computing Surveys57(5) (2025)

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.543459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e05b97b-e4a7-4a75-aceb-9b95bb2ec36c · outbound

This paper cites In: Confer- ence on Innovative Data Systems Research (CIDR) (2025),https://www.vldb.

Data Quality Profiling at Scale with Progressive Sampling: A Benchmark for Data-Centric AI Pipelines In: Confer- ence on Innovative Data Systems Research (CIDR) (2025),https://www.vldb

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-01T02:42:55.545446Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.