https://github.com/johntiger1/multimodal_fairness
공식 코드Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation
Fairness-Enhancing Ensemble Classification in Water Distribution Networks
Reproducibility Study Of Learning Fair Graph Representations Via Automated Data Augmentations
A Large-Scale Empirical Study on Improving the Fairness of Image Classification Models
BSL: Understanding and Improving Softmax Loss for Recommendation
AudioTrust: Benchmarking the Multifaceted Trustworthiness of Audio Large Language Models
A Stochastic Optimization Framework for Private and Fair Learning From Decentralized Data
Fair and Welfare-Efficient Constrained Multi-matchings under Uncertainty
FairStream: Fair Multimedia Streaming Benchmark for Reinforcement Learning Agents
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes
Can ChatGPT Assess Human Personalities? A General Evaluation Framework
On the Impact of Multi-dimensional Local Differential Privacy on Fairness
FaceXBench: Evaluating Multimodal LLMs on Face Understanding
MANI-Rank: Multiple Attribute and Intersectional Group Fairness for Consensus Ranking
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.