Exposure Fairness

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Most implemented papers archive 2025-07-28

8 shown of 8 papers with code (15 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Joint Multisided Exposure Fairness for Recommendation
  29 Apr 2022 2 repositories listed Syntology ran 7 of 9 samples · 2 unverified · 9 pointer-only (licence)
  Prior research on exposure fairness in the context of recommender systems has focused mostly on disparities in the exposure of individual or groups of items to individual users of the system.
• Joint Evaluation of Fairness and Relevance in Recommender Systems with Pareto Frontier
  17 Feb 2025 1 repository listed
  Motivated by this, we present a new approach for jointly evaluating fairness and relevance in RSs: Distance to Pareto Frontier (DPFR).
• Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits
  8 Aug 2024 1 repository listed
  In this paper, we study exposure bias in a class of well-known contextual bandit algorithms known as Linear Cascading Bandits.
• Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance
  28 May 2024 1 repository listed
  We find that most of these measures: i) correlate weakly with one another and even contradict each other at times; ii) are less sensitive to rank position changes than relevance- and fairness-only measures, meaning that…
• Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems
  22 Feb 2024 1 repository listed
  Typical recommendation and ranking methods aim to optimize the satisfaction of users, but they are often oblivious to their impact on the items (e.
• Simultaneously Achieving Group Exposure Fairness and Within-Group Meritocracy in Stochastic Bandits
  8 Feb 2024 1 repository listed
  At the first level, Bi-Level Fairness guarantees a certain minimum exposure to each group.
• Evaluation Measures of Individual Item Fairness for Recommender Systems: A Critical Study
  2 Nov 2023 1 repository listed
  To our knowledge, this is the first critical comparison of individual item fairness measures in recommender systems.
• FairGAN: GANs-based Fairness-aware Learning for Recommendations with Implicit Feedback
  25 Apr 2022 1 repository listed
  To fill this gap, we propose a Generative Adversarial Networks (GANs) based learning algorithm FairGAN mapping the exposure fairness issue to the problem of negative preferences in implicit feedback data.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.