SOTAVerified

Fairness

Papers

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Showing 2576–2600 of 5676 papers

TitleStatusHype
Re-formalization of Individual Fairness—0
Exploring Social Choice Mechanisms for Recommendation Fairness in SCRUFCode0
Flexible and Robust Counterfactual Explanations with Minimal Satisfiable PerturbationsCode0
Provider Fairness and Beyond-Accuracy Trade-offs in Recommender SystemsCode0
Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit RateCode0
Beyond XAI:Obstacles Towards Responsible AI—0
TIDE: Textual Identity Detection for Evaluating and Augmenting Classification and Language Models—0
Routing in Mixed Transportation Systems for Mobility Equity—0
VideolandGPT: A User Study on a Conversational Recommender System—0
Promoting Fairness in GNNs: A Characterization of Stability—0
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning—0
Developing A Fair Individualized Polysocial Risk Score (iPsRS) for Identifying Increased Social Risk of Hospitalizations in Patients with Type 2 Diabetes (T2D)—0
Towards Individual and Multistakeholder Fairness in Tourism Recommender Systems—0
Fairness Vs. Personalization: Towards Equity in Epistemic Utility—0
Fairness of Exposure in Dynamic Recommendation—0
Robust Recommender System: A Survey and Future DirectionsCode0
In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems—0
Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments—0
Interdisciplinary Fairness in Imbalanced Research Proposal Topic Inference: A Hierarchical Transformer-based Method with Selective Interpolation—0
Fairness in Ranking under Disparate UncertaintyCode0
CONFIDERAI: a novel CONFormal Interpretable-by-Design score function for Explainable and Reliable Artificial Intelligence—0
Bias Testing and Mitigation in LLM-based Code Generation—0
Approximating Fair k-Min-Sum-Radii in Euclidean Space—0
An explainable three dimension framework to uncover learning patterns: A unified look in variable sulci recognitionCode0
Fairness Implications of Heterogeneous Treatment Effect Estimation with Machine Learning Methods in Policy-making—0
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All datasetsBAF – BaseBAF – Variant IBAF – Variant IIBAF – Variant IIIBAF – Variant IVBAF – Variant VDiveFaceMORPHUTKFace

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