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Fairness

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보존된 평가 기록

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코드

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

https://github.com/moritzvz/ald

공식 코드

Locating disparities in machine learning

https://github.com/mostly-ai/mostlyai-engine

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TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data

https://github.com/mr-peach0301/flower

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Process-Supervised LLM Recommenders via Flow-guided Tuning

https://github.com/mr-ravin/collaborative-auction

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Addictive Auctions: using lucky-draw and gambling addiction to increase participation during auctioning

https://github.com/multifair-bandits/stochastic_fair_bandits

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Simultaneously Achieving Group Exposure Fairness and Within-Group Meritocracy in Stochastic Bandits

https://github.com/mycal-tucker/csn

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Prototype Based Classification from Hierarchy to Fairness

https://github.com/mymakar/causally_motivated_shortcut_removal

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Causally motivated Shortcut Removal Using Auxiliary Labels

https://github.com/nabenabe0928/meta-learn-tpe

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Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator

https://github.com/nabormendonca/gpt-4v-enade-cs-2021

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Evaluating ChatGPT-4 Vision on Brazil's National Undergraduate Computer Science Exam

https://github.com/nailashfrni/mcq-leakage-detection-code

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Simulating Training Data Leakage in Multiple-Choice Benchmarks for LLM Evaluation

https://github.com/nakpinar/diff-crime-reporting

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The effect of differential victim crime reporting on predictive policing systems

https://github.com/namhkoh/bad-bias-detection-in-llms

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BAD: BiAs Detection for Large Language Models in the context of candidate screening

https://github.com/namratadeka/circe

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Efficient Conditionally Invariant Representation Learning

https://github.com/nanaralala/density-based-correlated-equilibrium

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Learning Density-Based Correlated Equilibria for Markov Games

https://github.com/nandomp/missingFairness

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Fairness and Missing Values

https://github.com/nashory/rtic-gcn-pytorch

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RTIC: Residual Learning for Text and Image Composition using Graph Convolutional Network

https://github.com/natalialmg/MMPF

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Minimax Pareto Fairness: A Multi Objective Perspective

https://github.com/naveenr414/ijcai-rideshare

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Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling

https://github.com/naver-ai/cgl_fairness

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Learning Fair Classifiers with Partially Annotated Group Labels

https://github.com/naver/expohedron

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Introducing the Expohedron for Efficient Pareto-optimal Fairness-Utility Amortizations in Repeated Rankings

https://github.com/navid-naderi/Resilient_RRM_GNN

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Learning Resilient Radio Resource Management Policies with Graph Neural Networks

https://github.com/ncbi-nlp/llm-medicine-primer

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Demystifying Large Language Models for Medicine: A Primer

https://github.com/neeharperi/PreferenceNet

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PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning

https://github.com/neferpitou3871/ai-alignment-medical-imaging

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AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis

https://github.com/negar-mokhberian/aart

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Capturing Perspectives of Crowdsourced Annotators in Subjective Learning Tasks

https://github.com/nematgh/hetrofair

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Heterophily-Aware Fair Recommendation using Graph Convolutional Networks

https://github.com/neu-datamining/rocar

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RoCar: A Relationship Network-based Evaluation Method for Large Language Models

https://github.com/newbeeer/orthogonal_classifier

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Controlling Directions Orthogonal to a Classifier

https://github.com/newlei/FairGo

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Learning Fair Representations for Recommendation: A Graph-based Perspective

https://github.com/newlei/fda

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Improving Recommendation Fairness via Data Augmentation

https://github.com/nfriedri/debie-backend

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DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding Spaces

https://github.com/ngaggion/ubd_sourcecode

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Unsupervised bias discovery in medical image segmentation

https://github.com/ngoc-vien-dang/fairml-depression

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Fairness and bias correction in machine learning for depression prediction: results from four study populations

https://github.com/nick-jhlee/fair-manifold-pca

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Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold

https://github.com/niclui/diffusion-perturbations

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Leveraging Diffusion Perturbations for Measuring Fairness in Computer Vision

https://github.com/nicolasjulioflores/fair_algorithms_for_clustering

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Fair Algorithms for Clustering

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