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Fairness

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하위 태스크

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평가표

9

보존된 평가 기록

10

코드

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

https://github.com/ying1123/vtc-artifact

공식 코드

Fairness in Serving Large Language Models

https://github.com/yings0930/MAPPING

공식 코드

MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage

https://github.com/yingtaoluo/graph-of-gradient

공식 코드

Fairness without Demographics through Learning Graph of Gradients

https://github.com/yining-mao/moon-shape-icml-2023

공식 코드

Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations

https://github.com/yl489/social-bias-meets-data-bias

공식 코드

Social Bias Meets Data Bias: The Impacts of Labeling and Measurement Errors on Fairness Criteria

https://github.com/yliuaa/bnmr-faircompface

공식 코드

Component-Based Fairness in Face Attribute Classification with Bayesian Network-informed Meta Learning

https://github.com/yochem/bursting-the-burden-bubble

공식 코드

Bursting the Burden Bubble? An Assessment of Sharma et al.'s Counterfactual-based Fairness Metric

https://github.com/yoda-lab/simple-incentives-for-ridesharing

공식 코드

Using Simple Incentives to Improve Two-Sided Fairness in Ridesharing Systems

https://github.com/yonathanarbel/generativeinterpretation

공식 코드

Generative Interpretation

https://github.com/yongkdu/faircode

공식 코드

FairCoder: Evaluating Social Bias of LLMs in Code Generation

https://github.com/yongkdu/faircoder

공식 코드

FairCoder: Evaluating Social Bias of LLMs in Code Generation

https://github.com/youlei202/fairshap

공식 코드

FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation

https://github.com/youngmijin/fermge

공식 코드

A Fair Empirical Risk Minimization with Generalized Entropy

https://github.com/yromano/fair_dummies

공식 코드

Achieving Equalized Odds by Resampling Sensitive Attributes

https://github.com/ys-zong/medfair

공식 코드

MEDFAIR: Benchmarking Fairness for Medical Imaging

https://github.com/yuancheng-xu/elbert

공식 코드

Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate

https://github.com/yubol-cmu/awesome-multi-turn-llms

공식 코드

Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models

https://github.com/yuelin301/informationbargaining

공식 코드

Information Bargaining: Bilateral Commitment in Bayesian Persuasion

https://github.com/yuening-lab/f2gnn

공식 코드

Equipping Federated Graph Neural Networks with Structure-aware Group Fairness

https://github.com/yuhenglai/fairicp

공식 코드

FairICP: Encouraging Equalized Odds via Inverse Conditional Permutation

https://github.com/yuji-roh/fairbatch

공식 코드

FairBatch: Batch Selection for Model Fairness

https://github.com/yuji-roh/fr-train

공식 코드

FR-Train: A Mutual Information-Based Approach to Fair and Robust Training

https://github.com/yunqi-li/fairness-of-chatgpt

공식 코드

Fairness of ChatGPT

https://github.com/yunqi-li/personalized-counterfactual-fairness-in-recommendation

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Personalized Counterfactual Fairness in Recommendation

https://github.com/yushundong/elegant

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Certified Defense on the Fairness of Graph Neural Networks

https://github.com/yushundong/graph-mining-fairness-data

공식 코드

Fairness in Graph Mining: A Survey

https://github.com/yushundong/pygdebias

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Fairness in Graph Mining: A Survey

https://github.com/yushundong/referee

공식 코드

On Structural Explanation of Bias in Graph Neural Networks

https://github.com/yushundong/reliant

공식 코드

RELIANT: Fair Knowledge Distillation for Graph Neural Networks

https://github.com/yushuowiki/fairgt

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FairGT: A Fairness-aware Graph Transformer

https://github.com/yuwvandy/fairvgnn

공식 코드

Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage

https://github.com/yuyingzhao/fairexplanations-cfa

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Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations

https://github.com/yuyingzhao/simaug

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SimAug: Enhancing Recommendation with Pretrained Language Models for Dense and Balanced Data Augmentation

https://github.com/yuzhenmao/fairness-finetuning

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Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks

https://github.com/yvesrychener/Fair-FL

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Global Group Fairness in Federated Learning via Function Tracking

https://github.com/yw101004244/Understanding-Fairness-Surrogate-Functions

공식 코드

Understanding Fairness Surrogate Functions in Algorithmic Fairness

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