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Fairness
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/wi-pi/fairness_face_obfuscation
공식 코드Fairness Properties of Face Recognition and Obfuscation Systems
https://github.com/wiebket/sveva-fair
공식 코드SVEva Fair: A Framework for Evaluating Fairness in Speaker Verification
https://github.com/windxrz/DCFR
공식 코드https://github.com/wisdomshell/freeeval
공식 코드FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models
https://github.com/wish44165/ntd
공식 코드Data Stream Sampling with Fuzzy Task Boundaries and Noisy Labels
https://github.com/wissam-sib/calibrated_metrics
공식 코드https://github.com/wmgithub/fairness
공식 코드https://github.com/wnn2000/ffl4mia
공식 코드https://github.com/wnstlr/FACT
공식 코드https://github.com/wugl-cs/fairsort
공식 코드FairSort: Learning to Fair Rank for Personalized Recommendations in Two-Sided Platforms
https://github.com/wwweiwei/track2vec
공식 코드Track2Vec: fairness music recommendation with a GPU-free customizable-driven framework
https://github.com/wxqpxw/vfair
공식 코드Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
https://github.com/wyqing20/pfrec
공식 코드https://github.com/xfey/mctbench
공식 코드MCTBench: Multimodal Cognition towards Text-Rich Visual Scenes Benchmark
https://github.com/xianlizeng/bayes-optimal-fair-classification
공식 코드https://github.com/xianlizeng/fairbayes
공식 코드https://github.com/xianlizeng/fairbayes-ddp-plus
공식 코드Minimax Optimal Fair Classification with Bounded Demographic Disparity
https://github.com/xiaoleihuang/Multilingual_Fairness_LREC
공식 코드Multilingual Twitter Corpus and Baselines for Evaluating Demographic Bias in Hate Speech Recognition
https://github.com/xiaolin-cs/bemap
공식 코드BeMap: Balanced Message Passing for Fair Graph Neural Network
https://github.com/xiaoni-61/dh-benchmark
공식 코드Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning
https://github.com/xiaoyuxin1002/bias_in_deid
공식 코드In the Name of Fairness: Assessing the Bias in Clinical Record De-identification
https://github.com/xinyi-0724/gtfs_transpowernet
공식 코드https://github.com/xinyi-0724/kingcounty_24_node_virtual_power_grid
공식 코드https://github.com/xinyuelxy/bias-behind-the-wheel-fairness-testing-of-autonomous-driving-systems
공식 코드Bias Behind the Wheel: Fairness Testing of Autonomous Driving Systems
https://github.com/xiusu/Channel-Bench-Macro
공식 코드Searching for Network Width with Bilaterally Coupled Network
https://github.com/xiye7lai/cure4rec
공식 코드CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence
https://github.com/xiyuan-zhou/elecbench-a-power-dispatch-evaluation-benchmark-for-large-language-models
공식 코드ElecBench: a Power Dispatch Evaluation Benchmark for Large Language Models
https://github.com/xkianteb/ranking_constraints
공식 코드https://github.com/xlhex/dpnlp
공식 코드https://github.com/xmudm/dqabench
공식 코드Revolutionizing Database Q&A with Large Language Models: Comprehensive Benchmark and Evaluation
https://github.com/xqlin98/fair-yet-equal-cml
공식 코드https://github.com/xuchen0427/fairdiverse
공식 코드FairDiverse: A Comprehensive Toolkit for Fair and Diverse Information Retrieval Algorithms
https://github.com/xuchen0427/fairdual
공식 코드Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation
https://github.com/xuchen0427/fairsync
공식 코드FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval
https://github.com/xuchen0427/implicit_rank_unfairness
공식 코드A Study of Implicit Ranking Unfairness in Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.