SOTAVerified

Fairness

Papers

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Showing 601–650 of 5676 papers

TitleStatusHype
Marginal Fairness: Fair Decision-Making under Risk Measures—0
Soft Weighted Machine Unlearning—0
Smart Energy Guardian: A Hybrid Deep Learning Model for Detecting Fraudulent PV Generation—0
The Staircase of Ethics: Probing LLM Value Priorities through Multi-Step Induction to Complex Moral Dilemmas—0
Embracing Contradiction: Theoretical Inconsistency Will Not Impede the Road of Building Responsible AI Systems—0
Will Large Language Models Transform Clinical Prediction?—0
High-Fidelity Functional Ultrasound Reconstruction via A Visual Auto-Regressive Framework—0
Evaluating the Performance of Nigerian Lecturers using Multilayer Perceptron—0
Reasoning in Neurosymbolic AI—0
On the Deployment of RIS-mounted UAV Networks—0
Liouville PDE-based sliced-Wasserstein flow for fair regression—0
Reconsidering Fairness Through Unawareness from the Perspective of Model Multiplicity—0
AIDRIN 2.0: A Framework to Assess Data Readiness for AI—0
Accuracy vs. Accuracy: Computational Tradeoffs Between Classification Rates and Utility—0
Fairness under Competition—0
A Generic Framework for Conformal FairnessCode0
Internal and External Impacts of Natural Language Processing Papers—0
DISCO Balances the Scales: Adaptive Domain- and Difficulty-Aware Reinforcement Learning on Imbalanced Data—0
Cultural Value Alignment in Large Language Models: A Prompt-based Analysis of Schwartz Values in Gemini, ChatGPT, and DeepSeek—0
Evaluate Bias without Manual Test Sets: A Concept Representation Perspective for LLMs—0
Distributionally Robust Federated Learning with Client Drift Minimization—0
OpenEthics: A Comprehensive Ethical Evaluation of Open-Source Generative Large Language ModelsCode0
HAVA: Hybrid Approach to Value-Alignment through Reward Weighing for Reinforcement LearningCode0
Are the confidence scores of reviewers consistent with the review content? Evidence from top conference proceedings in AICode0
Mitigating Subgroup Disparities in Multi-Label Speech Emotion Recognition: A Pseudo-Labeling and Unsupervised Learning Approach—0
Unlearning Algorithmic Biases over Graphs—0
Explaining Neural Networks with ReasonsCode0
Algorithmic Hiring and Diversity: Reducing Human-Algorithm Similarity for Better Outcomes—0
Enforcing Hard Linear Constraints in Deep Learning Models with Decision Rules—0
DECASTE: Unveiling Caste Stereotypes in Large Language Models through Multi-Dimensional Bias Analysis—0
Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces—0
Adversarial Testing in LLMs: Insights into Decision-Making Vulnerabilities—0
Continuous Fair SMOTE -- Fairness-Aware Stream Learning from Imbalanced Data—0
Automated Bias Assessment in AI-Generated Educational Content Using CEAT FrameworkCode0
Aligning Trustworthy AI with Democracy: A Dual Taxonomy of Opportunities and Risks—0
Language Models That Walk the Talk: A Framework for Formal Fairness Certificates—0
Seeing the Unseen: How EMoE Unveils Bias in Text-to-Image Diffusion Models—0
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification—0
Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach—0
Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints—0
Teach2Eval: An Indirect Evaluation Method for LLM by Judging How It TeachesCode0
Interactional Fairness in LLM Multi-Agent Systems: An Evaluation Framework—0
Attribution Projection Calculus: A Novel Framework for Causal Inference in Bayesian Networks—0
Behind the Screens: Uncovering Bias in AI-Driven Video Interview Assessments Using Counterfactuals—0
Improving Fairness in LLMs Through Testing-Time Adversaries—0
HumaniBench: A Human-Centric Framework for Large Multimodal Models EvaluationCode0
Finding Counterfactual Evidences for Node ClassificationCode0
Equal is Not Always Fair: A New Perspective on Hyperspectral Representation Non-Uniformity—0
MPMA: Preference Manipulation Attack Against Model Context Protocol—0
Fairness-aware Anomaly Detection via Fair Projection—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