SOTAVerified

Fairness

Papers

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Showing 3301–3325 of 5676 papers

TitleStatusHype
Sequential Fair Resource Allocation under a Markov Decision Process Framework—0
se-Shweshwe Inspired Fashion Generation—0
Setting Fair Incentives to Maximize Improvement—0
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles—0
Shap-CAM: Visual Explanations for Convolutional Neural Networks based on Shapley Value—0
Shaping Up SHAP: Enhancing Stability through Layer-Wise Neighbor Selection—0
Shapley Sets: Feature Attribution via Recursive Function Decomposition—0
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning—0
Sharing the Load: Considering Fairness in De-energization Scheduling to Mitigate Wildfire Ignition Risk using Rolling Optimization—0
Shedding light on underrepresentation and Sampling Bias in machine learning—0
Shortcomings of Counterfactual Fairness and a Proposed Modification—0
Should Bank Stress Tests Be Fair?—0
Show, Don't Tell: Uncovering Implicit Character Portrayal using LLMs—0
SIG: A Synthetic Identity Generation Pipeline for Generating Evaluation Datasets for Face Recognition—0
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features—0
Significance of Chain of Thought in Gender Bias Mitigation for English-Dravidian Machine Translation—0
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification—0
SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models—0
Simple and Effective Specialized Representations for Fair Classifiers—0
Simple and near-optimal algorithms for hidden stratification and multi-group learning—0
Simplicity Bias Leads to Amplified Performance Disparities—0
Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability—0
Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations—0
Simultaneous Improvement of ML Model Fairness and Performance by Identifying Bias in Data—0
Single-loop Algorithms for Stochastic Non-convex Optimization with Weakly-Convex Constraints—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