Paper Citation Record · LEDGER

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models

As of 10 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2509.24340.

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

pith.paper-citation-record.v1
2509.24340 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T14:42:17.220465Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

14 of 14 outbound references displayed

verified exact1
verified fuzzy0
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b35ec638-ba5a-4ae8-a83d-f85ae119bfe2 · outbound

This paper cites Julia Angwin, Jeff Larson, Lauren Kirchner, and Surya Mattu.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models Julia Angwin, Jeff Larson, Lauren Kirchner, and Surya Mattu

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.029722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d998ef79-3d2d-4255-88e8-c763ca0eb797 · outbound

This paper cites Sample Complexity of Bias Detection with Subsampled Point-to-Subspace Distances.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models Sample Complexity of Bias Detection with Subsampled Point-to-Subspace Distances

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.175045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 059c5d22-50dd-405c-ba82-0355fca8edee · outbound

This paper cites ISBN 979-8-4007-1454-2.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models ISBN 979-8-4007-1454-2

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.185191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cc7607b-386f-4a19-a973-f312ecb7c55b · outbound

This paper cites Regulation (EU) 2024/1689.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models Regulation (EU) 2024/1689

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.189677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bea051a-795b-4f92-851c-c93a72b0db30 · outbound

This paper cites Dimitris Sacharidis, Giorgos Giannopoulos, George Papastefanatos, and Kostas Stefanidis.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models Dimitris Sacharidis, Giorgos Giannopoulos, George Papastefanatos, and Kostas Stefanidis

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.194089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa5873ab-5e42-4b56-bd60-50ccf8c8daf2 · outbound

This paper cites ISBN 979-8-4007-0330-0.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models ISBN 979-8-4007-0330-0

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.210366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba4d2a20-3a13-443d-923f-9cfb91570413 · outbound

This paper cites 9 Matilla, Nˇemeˇcek, Kryvoviaz, and Mareˇcek Quan Zhou, Ramen Ghosh, Robert Shorten, and Jakub Mareˇ cek.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models 9 Matilla, Nˇemeˇcek, Kryvoviaz, and Mareˇcek Quan Zhou, Ramen Ghosh, Robert Shorten, and Jakub Mareˇ cek

Reference 14

Resolution: verified exact; doi, observed 2026-08-04T14:43:32.519812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ee2b6908-65c0-49d1-b6f6-8741de0ed538 · outbound

This paper cites URLhttp://dx.doi.org/10.1109/ ICDEW61823.2024.00029.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models URLhttp://dx.doi.org/10.1109/ ICDEW61823.2024.00029

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.220465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb97866f-678e-4853-927e-19e9485624dd · outbound

This paper cites IEEE standard for algorithmic bias considerations.IEEE Std 7003-2024, pages 1–59,.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models IEEE standard for algorithmic bias considerations.IEEE Std 7003-2024, pages 1–59,

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.025373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d55077be-6da7-46ea-94d2-d8bb49b2aab5 · outbound

This paper cites Andrii Kliachkin, Eleni Psaroudaki, Jakub Marecek, and Dimitris Fotakis.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models Andrii Kliachkin, Eleni Psaroudaki, Jakub Marecek, and Dimitris Fotakis

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.034376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ba63a7b-23dd-4765-bb5c-5fbefe7abf62 · outbound

This paper cites doi: 10.1145/3457607.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models doi: 10.1145/3457607

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.180582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1af3d87-ae4a-46d3-9079-488c77385fa6 · outbound

This paper cites Ashish Sharma, Kevin Rushton, Inna Wanyin Lin, Theresa Nguyen, and Tim Althoff.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models Ashish Sharma, Kevin Rushton, Inna Wanyin Lin, Theresa Nguyen, and Tim Althoff

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.205457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fba3c502-5f76-4a75-9988-ad44e7990cd0 · outbound

This paper cites Auditing for Spatial Fairness.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models Auditing for Spatial Fairness

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.200460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 497342cf-5fb4-459e-bece-efc2fdc5533c · outbound

This paper cites Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Sch¨ olkopf, and Alexander Smola.

humancompatible.detect: a Python Toolkit for Detecting Bias in AI Models Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Sch¨ olkopf, and Alexander Smola

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:17.020136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.