Paper Citation Record · LEDGER

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms

As of 19 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2412.00424.

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

pith.paper-citation-record.v1
2412.00424 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:31:49.626804Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

47 of 47 outbound references displayed

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verified fuzzy42
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cadd1ad3-085c-44c4-89be-f09887a863d9 · outbound

This paper cites A clarification of the nuances in the fairness metrics landscape,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms A clarification of the nuances in the fairness metrics landscape,

Reference 1

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Observation 8363269b-a7e4-4687-9dbd-c328ae525d61 · outbound

This paper cites A survey on bias and fairness in machine learning,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms A survey on bias and fairness in machine learning,

Reference 2

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Observation fcde9c1e-5e00-47b5-b97d-117d3d5d4040 · outbound

This paper cites Recommendations as treatments: Debiasing learning and evaluation,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Recommendations as treatments: Debiasing learning and evaluation,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.248762Z

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Observation 9541b911-82a1-4af4-978a-994ecfe55256 · outbound

This paper cites Reinforced negative sampling for recommendation with exposure data.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Reinforced negative sampling for recommendation with exposure data

Reference 4

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Observation 6f32fed4-8666-47ed-b30a-dbdaa134583c · outbound

This paper cites Cascade model-based propen- sity estimation for counterfactual learning to rank,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Cascade model-based propen- sity estimation for counterfactual learning to rank,

Reference 5

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Observation 74636efd-84df-4dde-a1a6-5baf58d13892 · outbound

This paper cites Fair representation learning for recommendation: A mutual information perspective,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fair representation learning for recommendation: A mutual information perspective,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.210470Z

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Observation 947235f3-01da-485c-8481-51d5f24bd7d2 · outbound

This paper cites Fair representation learning for heterogeneous information networks,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fair representation learning for heterogeneous information networks,

Reference 7

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Source-reported events for the cited work

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Observation 967282b6-5e99-4c0c-96a5-3655ae38be67 · outbound

This paper cites Towards long-term fairness in recommendation,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Towards long-term fairness in recommendation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.183705Z

Source-reported events for the cited work

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Observation 72fd5bc1-4eed-45f4-83a1-c48d2b0a7a90 · outbound

This paper cites User-oriented fairness in recommendation,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms User-oriented fairness in recommendation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.170201Z

Source-reported events for the cited work

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Observation 15115a4e-3eaf-4870-ab95-8548b1f0ea9f · outbound

This paper cites Fairness-aware explainable recommendation over knowledge graphs,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fairness-aware explainable recommendation over knowledge graphs,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.157598Z

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Observation 23c4c9b4-6d62-467a-bba5-6ea1fb575cb6 · outbound

This paper cites Fairness among new items in cold start recommender systems,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fairness among new items in cold start recommender systems,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.142466Z

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Observation 78fb04eb-322b-4f0c-ae03-7043e6c8ae05 · outbound

This paper cites Fairness in recommendation ranking through pairwise comparisons,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fairness in recommendation ranking through pairwise comparisons,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.128895Z

Source-reported events for the cited work

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Observation 8728cd14-1485-466c-b30d-e44208b06a6b · outbound

This paper cites P- mmf: Provider max-min fairness re-ranking in recommender system,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms P- mmf: Provider max-min fairness re-ranking in recommender system,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.113727Z

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Observation f643ad9b-524a-4326-ab6e-69bf34f0d77d · outbound

This paper cites Fairrec: Two-sided fairness for personalized recom- mendations in two-sided platforms,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fairrec: Two-sided fairness for personalized recom- mendations in two-sided platforms,

Reference 14

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Observation 7b119596-df22-46f0-b327-fef70fab61b7 · outbound

This paper cites Tfrom: A two-sided fairness- aware recommendation model for both customers and providers,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Tfrom: A two-sided fairness- aware recommendation model for both customers and providers,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.087932Z

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Observation 3a8a0299-a451-43b4-ac4e-84a804be5621 · outbound

This paper cites Cpfair: Personalized consumer and producer fairness re-ranking for recommender systems,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Cpfair: Personalized consumer and producer fairness re-ranking for recommender systems,

Reference 16

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Observation e93e5902-f204-4282-ac0f-59b504e7bdf9 · outbound

This paper cites an unresolved cited work.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Unresolved cited work

Reference 17

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Observation 01c24f45-c3b3-4161-b3b9-3c9a48f30c04 · outbound

This paper cites Fairgan: Gans-based fairness-aware learning for recommendations with implicit feedback,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fairgan: Gans-based fairness-aware learning for recommendations with implicit feedback,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.053970Z

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Observation 0e1b2329-9a58-45d5-95a2-caf50fdc8819 · outbound

This paper cites Learning fair representations for recommendation: A graph-based perspective,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Learning fair representations for recommendation: A graph-based perspective,

Reference 19

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Observation 9dfd3268-4e3e-464d-8c12-6e8750b3353b · outbound

This paper cites Selective fairness in recommendation via prompts,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Selective fairness in recommendation via prompts,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.025818Z

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Observation 1c57a8be-ed78-4e8b-b37f-64d1ea1879f7 · outbound

This paper cites Make fairness more fair: Fair item utility estimation and exposure re-distribution,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Make fairness more fair: Fair item utility estimation and exposure re-distribution,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:50.011832Z

Source-reported events for the cited work

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Observation 6f5e93fc-cd48-42e9-8857-27a5ec1a4758 · outbound

This paper cites Fairness of exposure in light of in- complete exposure estimation,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fairness of exposure in light of in- complete exposure estimation,

Reference 22

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Observation 687df7c2-e2a8-4768-88e8-dbc93889c441 · outbound

This paper cites Toward a two-sided fairness framework in search and recommen- dation,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Toward a two-sided fairness framework in search and recommen- dation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.986385Z

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Observation 3e837554-0fcc-44cd-a182-2e5a2f1e31d1 · outbound

This paper cites Intersectional two-sided fairness in recommendation,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Intersectional two-sided fairness in recommendation,

Reference 24

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Observation 7687ead3-fa53-418a-9c9b-2e66d2fef45d · outbound

This paper cites Two-sided calibration for quality-aware responsible recommendation,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Two-sided calibration for quality-aware responsible recommendation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.958478Z

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Observation 4ec25470-5bb6-45c8-9b41-4730dcaed6f8 · outbound

This paper cites The combinatorial assignment problem: Approximate com- petitive equilibrium from equal incomes,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms The combinatorial assignment problem: Approximate com- petitive equilibrium from equal incomes,

Reference 26

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Observation 26e23b00-d175-45ea-a78a-a5c28b70ca28 · outbound

This paper cites User fairness, item fairness, and diversity for rankings in two-sided markets,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms User fairness, item fairness, and diversity for rankings in two-sided markets,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.921146Z

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Observation 495f0129-3eb0-4f0f-a93e-ab7f1d906dad · outbound

This paper cites Fairness constraints: A flexible approach for fair classification,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fairness constraints: A flexible approach for fair classification,

Reference 29

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Observation cecac04d-b2f2-410b-a64e-852bd4baf7d2 · outbound

This paper cites Satisfying real- world goals with dataset constraints,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Satisfying real- world goals with dataset constraints,

Reference 30

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This paper cites Fa* ir: A fair top-k ranking algorithm,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fa* ir: A fair top-k ranking algorithm,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.880836Z

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Observation dc1b3450-ea7c-4fa0-854e-b16439748c5a · outbound

This paper cites Equity of attention: Amortizing individual fairness in rankings,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Equity of attention: Amortizing individual fairness in rankings,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.933157Z

Source-reported events for the cited work

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Observation b3d85ecb-3c66-4247-a84a-cd3edda78582 · outbound

This paper cites Modeling Techniques for Machine Learning Fairness: A Survey.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Modeling Techniques for Machine Learning Fairness: A Survey

Reference 33

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Observation 50258bec-f803-49b9-9a1f-779198ef5947 · outbound

This paper cites Fairness in Machine Learning: A Survey.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fairness in Machine Learning: A Survey

Reference 34

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This paper cites Pollin, M.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Pollin, M

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.868036Z

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Observation d35a5ccb-93ba-489a-b483-8b215ea685e7 · outbound

This paper cites Minimum wage setting and standards of fairness,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Minimum wage setting and standards of fairness,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.854379Z

Source-reported events for the cited work

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Observation 1b949f10-faa6-4f80-a565-ded2547b26ec · outbound

This paper cites Fairness perceptions and reservation wages—the behavioral effects of minimum wage laws,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Fairness perceptions and reservation wages—the behavioral effects of minimum wage laws,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.839140Z

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Observation 48e8730c-7606-40fb-a064-e9eff41dda76 · outbound

This paper cites Earnings inequality and the minimum wage: Evidence from brazil,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Earnings inequality and the minimum wage: Evidence from brazil,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.826067Z

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Observation ebc1148b-0c01-4e85-a696-d0e211cec03f · outbound

This paper cites The effects of the minimum wage on earnings inequality: Evidence from china,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms The effects of the minimum wage on earnings inequality: Evidence from china,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.812995Z

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Observation 77be313e-2ff2-4f13-9b35-fa07bfc09302 · outbound

This paper cites Search engines that learn from implicit feedback,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Search engines that learn from implicit feedback,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.799567Z

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This paper cites Cumulated gain-based evaluation of ir techniques,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Cumulated gain-based evaluation of ir techniques,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.785986Z

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Observation e859823e-4eee-4305-997b-f81c0601c6fe · outbound

This paper cites Quicksort,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Quicksort,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T05:31:49.602179Z

Source-reported events for the cited work

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Observation ba21a4ff-ba4d-4384-b3ea-8011221d965b · outbound

This paper cites Addressing the cold-start problem in personalized flight ticket recommendation,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Addressing the cold-start problem in personalized flight ticket recommendation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.763758Z

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Observation 1ee70f99-f075-42e3-825c-e819f94fe028 · outbound

This paper cites Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.750207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9f4c951a-eae1-45ac-bc46-f7d48dd1a89a · outbound

This paper cites Factorization meets the item embedding: Regularizing matrix factorization with item co- occurrence,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Factorization meets the item embedding: Regularizing matrix factorization with item co- occurrence,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.736172Z

Source-reported events for the cited work

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Observation 34184ffb-e8a9-460f-aa4a-ff6a5bf71842 · outbound

This paper cites Location-based hierarchical matrix factorization for web service recommendation,.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Location-based hierarchical matrix factorization for web service recommendation,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.720696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 04bd0172-15c0-4978-8c50-68fa2301bf3b · outbound

This paper cites degree from Tianjin University, Tianjin, China, in 1996.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms degree from Tianjin University, Tianjin, China, in 1996

Reference 1965

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.705414Z

Source-reported events for the cited work

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Observation b034c98c-89f2-40a6-a6c8-640f0e6324b1 · outbound

This paper cites Xiao Xue (Member, IEEE) was born in 1979.

FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms Xiao Xue (Member, IEEE) was born in 1979

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:31:49.691119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.