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Paper Citation Record · LEDGER

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:1810.01943.

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

pith.paper-citation-record.v1
1810.01943 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 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 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:40:49.081675Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

268
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ad11937e-b3b1-4beb-aeba-85277350e7ec · inbound

Differential Parity: Relative Fairness Between Two Sets of Decisions cites this paper.

Differential Parity: Relative Fairness Between Two Sets of Decisions AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-05-24T12:06:10.936896Z

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.

source=pdf_text observed=2026-05-24T12:05:12.810169Z digest=sha256:67ab41bb342a32c6cc050464db8a8241cb0cc6288004644d07f35c0207728835

Observation 2f543b9b-717d-4931-a403-0e4eaf457b2f · inbound

Exploring a Behavioral Model of "Positive Friction" in Human-AI Interaction cites this paper.

Exploring a Behavioral Model of "Positive Friction" in Human-AI Interaction AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 2

Resolution
metadata mismatch
local_arxiv, observed 2026-05-24T03:53:55.502346Z

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.

source=pdf_text observed=2026-05-24T03:50:10.068369Z digest=sha256:9399664c5732c1ddeda81a40c9967f29bb35f00a32e85caa30f72298105054bd

Observation c28b8baa-638e-43f4-8d60-0935735d2505 · inbound

Advancing Responsible Innovation in Agentic AI: A study of Ethical Frameworks for Household Automation cites this paper.

Advancing Responsible Innovation in Agentic AI: A study of Ethical Frameworks for Household Automation AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T15:40:49.081675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:40:49.081675Z digest=sha256:d706a6b93e05c99d335396891c63b81bef8a1db55e07095250566181126e910d

Observation 2532275b-48fe-4a95-84c3-6b45bee8c2d9 · inbound

Helix 1.0: An Open-Source Framework for Reproducible and Interpretable Machine Learning on Tabular Scientific Data cites this paper.

Helix 1.0: An Open-Source Framework for Reproducible and Interpretable Machine Learning on Tabular Scientific Data AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T14:52:24.255981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:52:24.255981Z digest=sha256:fc2889ec7623c7a3f5c400dea8be2444070b9c365ff9f5c3709851ee2237d7af

Observation 7088de15-d97d-4cbd-bf11-d52eec3a2371 · inbound

Development of management systems using artificial intelligence systems and machine learning methods for boards of directors (preprint, unofficial translation) cites this paper.

Development of management systems using artificial intelligence systems and machine learning methods for boards of directors (preprint, unofficial translation) AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-06T04:45:51.131600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:45:51.131600Z digest=sha256:a1944a2e4221a65f85ee27e611bfc478e4cd606f120bd65c39ee463887c10a69

Observation a5028ac7-b93e-46a3-82b4-25e1a3b506ca · inbound

Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing cites this paper.

Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T20:07:03.313142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:07:03.313142Z digest=sha256:6235054743d3a860b0d425b0f720d056d7a412081730cad260fba37e700f78e0

Observation ef7542e2-9e0c-4d7a-ba1b-971aebdd1d7b · inbound

CaTE Data Curation for Trustworthy AI cites this paper.

CaTE Data Curation for Trustworthy AI AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T18:23:20.597315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:23:20.597315Z digest=sha256:ed3e7aab5e3c6da5a8dd2313c38d491e094717af9758a9c8d9185340aa5aee2e

Observation 7a22b835-0d02-4a70-9e86-349e484bad78 · inbound

Revisiting Pre-processing Group Fairness: A Modular Benchmarking Framework cites this paper.

Revisiting Pre-processing Group Fairness: A Modular Benchmarking Framework AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T18:07:49.447735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:07:49.447735Z digest=sha256:17cf57bf8414d95e55fee5174b02fe80de7f7f2068cc12db62e62508bb785f05

Observation 2ce21c2a-802f-43ac-9653-b4911fe44f0e · inbound

InsightBoard: An Interactive Multi-Metric Visualization and Fairness Analysis Plugin for TensorBoard cites this paper.

InsightBoard: An Interactive Multi-Metric Visualization and Fairness Analysis Plugin for TensorBoard AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T20:53:16.184967Z

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.

source=pdf_text observed=2026-05-13T20:49:15.553065Z digest=sha256:c88d7bf99cba9504c913347c4201310eaca0aeaa441edde60fd6e4684a62de1d

Observation ba7cb723-d81e-40ae-aab4-a582ef65442c · inbound

FairLogue: A Toolkit for Intersectional Fairness Analysis in Clinical Machine Learning Models cites this paper.

FairLogue: A Toolkit for Intersectional Fairness Analysis in Clinical Machine Learning Models AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:10:49.012072Z

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.

source=arxiv_source observed=2026-05-10T20:11:04.940371Z digest=sha256:f820ca601c355dd77945ce5032ab95826366f52a253de1478afee1c991afd5d5

Observation dac9dad4-870c-4f38-808f-dfec8f11bea3 · inbound

Towards Reliable Testing of Machine Unlearning cites this paper.

Towards Reliable Testing of Machine Unlearning AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:25:18.336562Z

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.

source=pdf_text observed=2026-05-10T11:24:29.533446Z digest=sha256:faafc011f7ccdf273c4e34e314e16da37cdafaf5b932cf4d60aaf9fb6b0b9282

Observation 27089819-02ff-4feb-b251-fe67fc2d5b74 · inbound

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics cites this paper.

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-20T14:28:21.481305Z

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.

source=pdf_text observed=2026-05-20T14:25:15.565386Z digest=sha256:4885b2e30ec468721ae439ea7b5d60964df685cd5df34107093cabb8f8762c10

Observation c6da752b-3abb-4898-8614-daaecae144d8 · inbound

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics cites this paper.

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-06-30T19:05:00.895440Z

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.

source=pdf_text observed=2026-06-30T19:00:30.961402Z digest=sha256:080ed380f048298da9e95d61747c26066b1b49d46667a02f965a1df74021bc2d

Observation ed48d931-143a-4199-97bc-5b661fd1891d · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 127

Resolution
verified exact
local_arxiv, observed 2026-06-28T07:11:45.011634Z

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.

source=arxiv_source observed=2026-06-28T07:05:18.026601Z digest=sha256:afca98ace84b70dc3fe1827942960ed3915ce413c1f5009a8f1e04a1707047b8

Observation c202f74d-9702-4012-a8ba-dcb4d820763b · inbound

Beyond Third-Person Audits: Situated Interaction Auditing for User-Centered LLM Bias Research cites this paper.

Beyond Third-Person Audits: Situated Interaction Auditing for User-Centered LLM Bias Research AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 12

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T13:28:18.911008Z

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.

source=arxiv_source observed=2026-06-27T08:03:18.763513Z digest=sha256:12966278718f200538df038a05408928e2c00a8003b7d6fde6567e7dab401498

Observation bb9ea3a3-caf7-4e7e-a97b-f3c87530dc39 · inbound

The Unseen Hand: Manipulating Model Fairness and SHAP with Targeted Identity Re-Association Attacks cites this paper.

The Unseen Hand: Manipulating Model Fairness and SHAP with Targeted Identity Re-Association Attacks AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-07-04T10:09:44.814229Z

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.

source=pdf_text observed=2026-06-26T09:07:42.347940Z digest=sha256:2f8de830429a67d61a8710edfef32a61b099117a9df35f573ddf8cb3627bd13d

Observation beaf34d5-cada-4f9f-9ea2-0c8477825c2f · inbound

FairBED: A Bayesian Experimental Design Approach to Gathering Fairer Data cites this paper.

FairBED: A Bayesian Experimental Design Approach to Gathering Fairer Data AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-07-04T12:49:51.971094Z

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.

source=pdf_text observed=2026-06-26T06:07:45.509382Z digest=sha256:25ddfdc140906d6758552bd626256a6d199151a7aae0909a40edf43056de930d

Observation ea9d31cc-a48b-47b0-aae9-b3003b9f5617 · inbound

FairSelect: A Systematic Evaluation of Multi-Level and Intersectional Algorithmic Fairness cites this paper.

FairSelect: A Systematic Evaluation of Multi-Level and Intersectional Algorithmic Fairness AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 20

Resolution
unresolved
no resolver link, observed 2026-07-13T05:33:08.548804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T05:33:08.548804Z digest=sha256:fb167d98abd48837f12b5e774cc9600b05be8bf8bfe33d7f6bda48c3c373114b

Observation 8bfd89f2-5795-42c5-8f3e-381c23f28b54 · inbound

FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents cites this paper.

FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-03T16:50:33.973069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T16:50:33.973069Z digest=sha256:7d27bab9303624f9138ff753d3cd0a63318f7c7fd63044e5cdeb2eae69437d5e