SOTAVerified

Fairness

Papers

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Showing 4851–4875 of 5676 papers

TitleStatusHype
Counterfactual Fair Opportunity: Measuring Decision Model Fairness with Counterfactual Reasoning—0
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals—0
Counterfactually Fair Regression with Double Machine Learning—0
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing—0
Counterfactual Multi-Token Fairness in Text Classification—0
Counterfactual Reasoning for Fair Clinical Risk Prediction—0
Integrating Fairness and Model Pruning Through Bi-level Optimization—0
CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition—0
Covariance-Robust Dynamic Watermarking—0
Coverage and Spectral Efficiency of NOMA-Enabled LEO Satellite Networks with Ordering Schemes—0
Creating a Discipline-specific Commons for Infectious Disease Epidemiology—0
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk—0
Credit Risk Meets Large Language Models: Building a Risk Indicator from Loan Descriptions in P2P Lending—0
Critical windows: non-asymptotic theory for feature emergence in diffusion models—0
Cross Layer Optimization and Distributed Reinforcement Learning for Wireless 360° Video Streaming—0
Cross-utterance ASR Rescoring with Graph-based Label Propagation—0
Crowd, Lending, Machine, and Bias—0
Crowd-SFT: Crowdsourcing for LLM Alignment—0
Crowdsourcing with Fairness, Diversity and Budget Constraints—0
Cubic-Regularized Newton for Spectral Constrained Matrix Optimization and its Application to Fairness—0
CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms—0
Cultural Re-contextualization of Fairness Research in Language Technologies in India—0
Cultural Value Alignment in Large Language Models: A Prompt-based Analysis of Schwartz Values in Gemini, ChatGPT, and DeepSeek—0
CUPID: Improving Battle Fairness and Position Satisfaction in Online MOBA Games with a Re-matchmaking System—0
Current state of LLM Risks and AI Guardrails—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