SOTAVerified

Fairness

Papers

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Showing 3926–3950 of 5676 papers

TitleStatusHype
What is the Point of Fairness? Disability, AI and The Complexity of Justice—0
What Role Do Intelligent Reflecting Surfaces Play in Multi-Antenna Non-Orthogonal Multiple Access?—0
What Should We Optimize in Participatory Budgeting? An Experimental Study—0
What's in a Query: Polarity-Aware Distribution-Based Fair Ranking—0
What's Sex Got To Do With Fair Machine Learning?—0
What's the Problem, Linda? The Conjunction Fallacy as a Fairness Problem—0
"What We Can't Measure, We Can't Understand": Challenges to Demographic Data Procurement in the Pursuit of Fairness—0
What will it take to generate fairness-preserving explanations?—0
When Can Memorization Improve Fairness?—0
Whence Is A Model Fair? Fixing Fairness Bugs via Propensity Score Matching—0
When Collaborative Filtering is not Collaborative: Unfairness of PCA for Recommendations—0
When Counterfactual Reasoning Fails: Chaos and Real-World Complexity—0
When does a predictor know its own loss?—0
Does Data Augmentation Improve Generalization in NLP?—0
When Fairness Isn't Statistical: The Limits of Machine Learning in Evaluating Legal Reasoning—0
When the Umpire is also a Player: Bias in Private Label Product Recommendations on E-commerce Marketplaces—0
When Transliteration Met Crowdsourcing : An Empirical Study of Transliteration via Crowdsourcing using Efficient, Non-redundant and Fair Quality Control—0
When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness—0
Where Are We? Using Scopus to Map the Literature at the Intersection Between Artificial Intelligence and Research on Crime—0
Where Is the Normative Proof? Assumptions and Contradictions in ML Fairness Research—0
Where to locate COVID-19 mass vaccination facilities?—0
Which Demographic Features Are Relevant for Individual Fairness Evaluation of U.S. Recidivism Risk Assessment Tools?—0
Whistleblower protection in the digital age -- why 'anonymous' is not enough. From technology to a wider view of governance—0
Whither Bias Goes, I Will Go: An Integrative, Systematic Review of Algorithmic Bias Mitigation—0
Whither Fair Clustering?—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)99.86—Unverified
21D-CSNNPredictive Equality (age)97.8—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)96.87—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)98.97—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)98.45—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)98.68—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)99.31—Unverified
#ModelMetricClaimedVerifiedStatus
1Neighbour LearningDegree of Bias (DoB)0.49—Unverified
#ModelMetricClaimedVerifiedStatus
1Neighbour LearningDegree of Bias (DoB)6.26—Unverified
#ModelMetricClaimedVerifiedStatus
1Neighbour LearningDegree of Bias (DoB)1.96—Unverified