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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/ucsc-real/fairness_transferability

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Fairness Transferability Subject to Bounded Distribution Shift

https://github.com/ucsc-real/fairnesswithoutharm

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Fairness Without Harm: An Influence-Guided Active Sampling Approach

https://github.com/uds-lsv/gender-country-occupation-biases

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Colombian Waitresses y Jueces canadienses: Gender and Country Biases in Occupation Recommendations from LLMs

https://github.com/uds-lsv/stereokg

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StereoKG: Data-Driven Knowledge Graph Construction for Cultural Knowledge and Stereotypes

https://github.com/uewopq88/Reckoner-Fairness

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Fairness without Sensitive Attributes via Knowledge Sharing

https://github.com/uhlerlab/infocore

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Removing Biases from Molecular Representations via Information Maximization

https://github.com/uic-indexlab/chameleon

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Chameleon: Foundation Models for Fairness-aware Multi-modal Data Augmentation to Enhance Coverage of Minorities

https://github.com/uic-indexlab/fair_entity_matching

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Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching

https://github.com/uic-indexlab/fairemdemo

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FairEM360: A Suite for Responsible Entity Matching

https://github.com/uiuc-focal-lab/IVAN

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Incremental Verification of Neural Networks

https://github.com/uiuctml/fair-classification

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A Unified Post-Processing Framework for Group Fairness in Classification

https://github.com/umangsbhatt/divine-release

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DIVINE: Diverse Influential Training Points for Data Visualization and Model Refinement

https://github.com/umd-huang-lab/elbert

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

https://github.com/umd-huang-lab/transfer-fairness

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Transferring Fairness under Distribution Shifts via Fair Consistency Regularization

https://github.com/umgupta/fairness-via-contrastive-estimation

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Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation

https://github.com/unitn-sml/wmi-pa

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Enhancing SMT-based Weighted Model Integration by Structure Awareness

https://github.com/urielsinger/eqgnn

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EqGNN: Equalized Node Opportunity in Graphs

https://github.com/usaito/kdd2022-fair-ranking-nsw

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Fair Ranking as Fair Division: Impact-Based Individual Fairness in Ranking

https://github.com/usmangohar/fairensemble

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Towards Understanding Fairness and its Composition in Ensemble Machine Learning

https://github.com/ustunb/ctfdist

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Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions

https://github.com/uthaipon/multi-criteria-dimensionality-reduction

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Multi-Criteria Dimensionality Reduction with Applications to Fairness

https://github.com/uzn36/attributeswitching

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Fair Sampling in Diffusion Models through Switching Mechanism

https://github.com/vahini01/indiandemographics

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Decoding Demographic un-fairness from Indian Names

https://github.com/val-iisc/selmix

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Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives

https://github.com/vanbanTruong/FAHT

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FAHT: An Adaptive Fairness-aware Decision Tree Classifier

https://github.com/vanbantruong/fairness-in-large-language-models

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Datasets for Fairness in Language Models: An In-Depth Survey

https://github.com/vanderschaarlab/decaf

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DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks

https://github.com/vanderschaarlab/survivalgan

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SurvivalGAN: Generating Time-to-Event Data for Survival Analysis

https://github.com/vanderschaarlab/synthcity

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Synthcity: facilitating innovative use cases of synthetic data in different data modalities

https://github.com/vaseline555/aaggff

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Pursuing Overall Welfare in Federated Learning through Sequential Decision Making

https://github.com/vatsalsharan/multigroup-kl

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KL Divergence Estimation with Multi-group Attribution

https://github.com/vcbsl-fairness/fineface

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FineFACE: Fair Facial Attribute Classification Leveraging Fine-grained Features

https://github.com/vdasu/neufair

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NeuFair: Neural Network Fairness Repair with Dropout

https://github.com/vectorinstitute/humanibench

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HumaniBench: A Human-Centric Framework for Large Multimodal Models Evaluation

https://github.com/vectorinstitute/recommender-systems-survey

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A Comprehensive Review of Recommender Systems: Transitioning from Theory to Practice

https://github.com/vengdeng/fcro

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On Fairness of Medical Image Classification with Multiple Sensitive Attributes via Learning Orthogonal Representations

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