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Paper Citation Record · LEDGER

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes

As of 21 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2608.10470.

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

pith.paper-citation-record.v1
2608.10470 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:25:23.319288Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

38 of 38 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a3395934-0d58-4c79-846d-f93321d680cb · outbound

This paper cites Adaptive test of independence based on HSIC measures.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Adaptive test of independence based on HSIC measures

Reference 1

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Observation 7ca45ab4-c319-4f23-9248-de451d4147b0 · outbound

This paper cites Machine bias.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Machine bias

Reference 2

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Observation ae2a5ab6-8aba-4c34-9a45-f51a829c24c6 · outbound

This paper cites Three naive B ayes approaches for discrimination-free classification.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Three naive B ayes approaches for discrimination-free classification

Reference 3

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Observation cb85a282-4daa-44f8-a7ff-7455fec73db7 · outbound

This paper cites A fair classifier using kernel density estimation.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes A fair classifier using kernel density estimation

Reference 4

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Observation 6eabcb17-915c-4660-a7a5-3d9e4cce6355 · outbound

This paper cites A fair classifier using mutual information.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes A fair classifier using mutual information

Reference 5

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Source-reported events for the cited work

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Observation 791f74af-5051-4d5a-93f7-a685bb7a4359 · outbound

This paper cites Cover and Joy A.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Cover and Joy A

Reference 6

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Source-reported events for the cited work

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Observation b7a244af-6f7c-4666-a3dc-3ab31f1c73a5 · outbound

This paper cites Flexibly fair representation learning by disentanglement.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Flexibly fair representation learning by disentanglement

Reference 7

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Source-reported events for the cited work

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Observation 21570716-76a4-4783-a3f0-50388ac28fc2 · outbound

This paper cites MMD-B-Fair : Learning fair representations with statistical testing.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes MMD-B-Fair : Learning fair representations with statistical testing

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 8efa0529-dfdd-4cc1-be3d-62a1bdfa641b · outbound

This paper cites Retiring adult: New datasets for fair machine learning.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Retiring adult: New datasets for fair machine learning

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b5f3ceb6-388a-4c85-a102-6b475731fcbe · outbound

This paper cites Bach, and Arthur Gretton.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Bach, and Arthur Gretton

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 77a1a1fe-bb39-4a2f-b36d-0074b1cf4ed6 · outbound

This paper cites Fairness without the sensitive attribute via causal variational autoencoder.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Fairness without the sensitive attribute via causal variational autoencoder

Reference 11

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Observation cf8e02d3-0075-4651-88d9-43ebe844f704 · outbound

This paper cites Measuring statistical dependence with Hilbert-Schmidt norms.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Measuring statistical dependence with Hilbert-Schmidt norms

Reference 12

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Source-reported events for the cited work

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Observation 3233c146-b521-4d16-880d-c9b3692eb473 · outbound

This paper cites A kernel statistical test of independence.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes A kernel statistical test of independence

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation e7d0546f-68d5-4961-80c5-ef127f876f42 · outbound

This paper cites A kernel two-sample test.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes A kernel two-sample test

Reference 14

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Source-reported events for the cited work

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Observation d985de68-c5e5-4c3c-9ed2-66bbdd39bc6d · outbound

This paper cites Generalized demographic parity for group fairness.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Generalized demographic parity for group fairness

Reference 15

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Source-reported events for the cited work

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Observation 794544d1-cc4d-4330-a1d1-22f61e109524 · outbound

This paper cites Foundations of Modern Probability.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Foundations of Modern Probability

Reference 16

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 13fe3d78-5562-4563-bc05-ed3c67edca07 · outbound

This paper cites Random matrix approximation of spectra of integral operators.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Random matrix approximation of spectra of integral operators

Reference 17

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Source-reported events for the cited work

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Observation 0b287b60-5d75-492c-8cdd-13876ea56734 · outbound

This paper cites Fair representation learning for continuous sensitive attributes using expectation of integral probability metrics.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Fair representation learning for continuous sensitive attributes using expectation of integral probability metrics

Reference 18

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Source-reported events for the cited work

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Observation aa082568-607e-4350-9bf0-3e90914e9d1f · outbound

This paper cites Counterfactual fairness.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Counterfactual fairness

Reference 19

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Source-reported events for the cited work

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Observation 8499bfc6-cc77-47a7-a1d8-785ef32cbf08 · outbound

This paper cites Kernel dependence regularizers and Gaussian processes with applications to algorithmic fairness.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Kernel dependence regularizers and Gaussian processes with applications to algorithmic fairness

Reference 20

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Source-reported events for the cited work

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Observation aaa6a58a-9fad-403c-ba03-e5d0f01a5ed5 · outbound

This paper cites The variational fair autoencoder.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes The variational fair autoencoder

Reference 21

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Source-reported events for the cited work

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Observation 34c83bc4-6db9-423a-9f84-83440c5a418d · outbound

This paper cites The HSIC bottleneck: Deep learning without back-propagation.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes The HSIC bottleneck: Deep learning without back-propagation

Reference 22

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Source-reported events for the cited work

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Observation 9194083c-a82b-4b74-a73e-8ed9ece5ee49 · outbound

This paper cites Nonlinear dimensionality reduction based on HSIC maximization.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Nonlinear dimensionality reduction based on HSIC maximization

Reference 23

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Observation 8182b423-52a6-4039-b4a4-96911ea18bc7 · outbound

This paper cites Learning adversarially fair and transferable representations.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Learning adversarially fair and transferable representations

Reference 24

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Source-reported events for the cited work

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Observation 25023e30-5a17-4032-9aa1-c8ca768e01ae · outbound

This paper cites Fairness-aware learning for continuous attributes and treatments.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Fairness-aware learning for continuous attributes and treatments

Reference 25

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Source-reported events for the cited work

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Observation 2dd76ae1-aa53-4942-867d-7d1938d6829d · outbound

This paper cites On estimating regression.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes On estimating regression

Reference 26

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Source-reported events for the cited work

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Observation b5bd3b23-6b0c-4109-a315-47f27e3a76ef · outbound

This paper cites A Uniform Concentration Inequality for Kernel-Based Two-Sample Statistics.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes A Uniform Concentration Inequality for Kernel-Based Two-Sample Statistics

Reference 27

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Source-reported events for the cited work

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Observation ff0bb186-590e-413a-981b-170d25cf9988 · outbound

This paper cites Causality: Models, Reasoning, and Inference.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Causality: Models, Reasoning, and Inference

Reference 28

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Source-reported events for the cited work

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Observation 787951a1-5a76-416f-a553-c6c2994cd3c0 · outbound

This paper cites Fair kernel learning.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Fair kernel learning

Reference 29

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Source-reported events for the cited work

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Observation d1af92c3-586a-4708-9ffb-cfe329cbac24 · outbound

This paper cites Discovering fair representations in the data domain.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Discovering fair representations in the data domain

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 842478cb-fbff-426c-a178-83b3d079f62e · outbound

This paper cites Achieving equalized odds by resampling sensitive attributes.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Achieving equalized odds by resampling sensitive attributes

Reference 31

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Source-reported events for the cited work

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Observation 94cbccb7-f526-4209-b8b7-6c318f167461 · outbound

This paper cites Equivalence of distance-based and RKHS -based statistics in hypothesis testing.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Equivalence of distance-based and RKHS -based statistics in hypothesis testing

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 1487b69b-981a-4625-a42f-69ce2fb1d5e4 · outbound

This paper cites Supervised feature selection via dependence estimation.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Supervised feature selection via dependence estimation

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 46770111-2222-497a-8b69-c5152622cdd0 · outbound

This paper cites Feature selection via dependence maximization.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Feature selection via dependence maximization

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 91a76298-178a-4d34-baaa-7669ed03deb7 · outbound

This paper cites Characteristic and universal tensor product kernels.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Characteristic and universal tensor product kernels

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 2026-08-20T06:33:59.587034+00:00.

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Observation ef71c681-081a-4168-b857-8fd4bf1a8b68 · outbound

This paper cites Measuring and testing dependence by correlation of distances.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Measuring and testing dependence by correlation of distances

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-15T14:25:23.377906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T14:25:23.312537Z digest=sha256:76e464b34c7f9a6d4ded7eb6575a67e3240101c0d12c66daa50dc31079494f18

Observation b2279cd7-5680-4566-9190-28a52ece9272 · outbound

This paper cites Smooth regression analysis.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Smooth regression analysis

Reference 37

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source=arxiv_source observed=2026-08-15T14:25:23.315825Z digest=sha256:71763641c1fd4445e5f5a05356bf576efeff34e84513f99a11d876b3afdd1d2a

Observation baabedb0-49fd-43c5-9d6d-23a930acdeb8 · outbound

This paper cites Learning fair representations.

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes Learning fair representations

Reference 38

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no resolver link, observed 2026-08-15T14:25:23.319288Z

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source=arxiv_source observed=2026-08-15T14:25:23.319288Z digest=sha256:d2719a764d162af465858d0bd051ca5a8a27ab2a822e4e25078df68b0435c9e4

Pith citing papers

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