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Fairness

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/BradSegal/ClinicalDataSimulator

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Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation

https://github.com/CN-TU/reinforcement-learning-for-per-flow-buffer-sizing

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LFQ: Online Learning of Per-flow Queuing Policies using Deep Reinforcement Learning

https://github.com/CPJKU/information_retrieval_fairness_debiasing

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Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers

https://github.com/CSHaitao/CalibraEval

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CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges

https://github.com/CalebFikes/MCRAGE-Emory_Math_REU_2023

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MCRAGE: Synthetic Healthcare Data for Fairness

https://github.com/CausalML/xauc

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The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric

https://github.com/Chenglu0426/FairGraphFL

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Towards Fair Graph Federated Learning via Incentive Mechanisms

https://github.com/ChenlongDeng/KELLER

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Learning Interpretable Legal Case Retrieval via Knowledge-Guided Case Reformulation

https://github.com/ChunaraLab/FairDCL-mitigating-urban-rural-disparity

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Mitigating Urban-Rural Disparities in Contrastive Representation Learning with Satellite Imagery

https://github.com/CogComp/iclr_database

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Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach

https://github.com/Computer-Vision-in-the-Wild/Elevater_Toolkit_IC

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ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models

https://github.com/ComputerVisionIUST/IUST_PersonReId

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IUST_PersonReId: A New Domain in Person Re-Identification Datasets

https://github.com/CyberAgentAILab/FairReciprocalRecommendation

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Fair Reciprocal Recommendation in Matching Markets

https://github.com/DUT-lujunyu/Debias

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Take its Essence, Discard its Dross! Debiasing for Toxic Language Detection via Counterfactual Causal Effect

https://github.com/DataResponsibly/CIFRank

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Causal intersectionality for fair ranking

https://github.com/DrugLT/ImDrug

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ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery

https://github.com/Echoslayer/XAI_From_Classical_Models_to_LLMs

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A Comprehensive Guide to Explainable AI: From Classical Models to LLMs

https://github.com/EdenBelouadah/class-incremental-learning

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Initial Classifier Weights Replay for Memoryless Class Incremental Learning

https://github.com/ElementAI/active-fairness

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Can Active Learning Preemptively Mitigate Fairness Issues?

https://github.com/EnderGed/FairGCN

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Fairness and/or Privacy on Social Graphs

https://github.com/EnyanDai/FairGNN

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Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information

https://github.com/EricP66/Automated-Word-Extraction

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Automated Bias Assessment in AI-Generated Educational Content Using CEAT Framework

https://github.com/FMZennaro/Fair-Pooling-Causal-Models

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Counterfactually Fair Prediction Using Multiple Causal Models

https://github.com/FairMedFM/FairMedFM

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FairMedFM: Fairness Benchmarking for Medical Imaging Foundation Models

https://github.com/Faldict/fair-classification-with-noisy-labels

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Fair Classification with Group-Dependent Label Noise

https://github.com/FarrandTom/deep-learning-fairness

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Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy

https://github.com/FlorianRupp/pcgrl-simulation-driven-balancing

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Simulation-Driven Balancing of Competitive Game Levels with Reinforcement Learning

https://github.com/FraFabbri/fair-subset-datastream

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Fair and Representative Subset Selection from Data Streams

https://github.com/Gp1g/RFL

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FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning

https://github.com/Greilfang/Loss-Tolerant-Federated-Learning

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Loss Tolerant Federated Learning

https://github.com/Grey-z/FairAgent

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Enhancing New-item Fairness in Dynamic Recommender Systems

https://github.com/GuilhermePelegrina/mofpca

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Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective Optimization

https://github.com/HKUST-KnowComp/Fair_HIN

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Fair Representation Learning for Heterogeneous Information Networks

https://github.com/HanXudong/fairlib

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Towards Equal Opportunity Fairness through Adversarial Learning

https://github.com/Haoran-S/ICASSP2021

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Learning to Continuously Optimize Wireless Resource In Episodically Dynamic Environment

https://github.com/Haoran-S/TSP_CL

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Learning to Continuously Optimize Wireless Resource in a Dynamic Environment: A Bilevel Optimization Perspective

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