"bias mitigation" Papers
21 papers found
Conference
Adversarial Latent Feature Augmentation for Fairness
Hoin Jung, Junyi Chai, Xiaoqian Wang
ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition
Joseph Fioresi, Ishan Rajendrakumar Dave, Mubarak Shah
Controllable Feature Whitening for Hyperparameter-Free Bias Mitigation
Yooshin Cho, Hanbyel Cho, Janghyeon Lee et al.
EvA: Erasing Spurious Correlations with Activations
Qiyuan He, Kai Xu, Angela Yao
FairImagen: Post-Processing for Bias Mitigation in Text-to-Image Models
Zihao Fu, Ryan Brown, Shun Shao et al.
LCGC: Learning from Consistency Gradient Conflicting for Class-Imbalanced Semi-Supervised Debiasing
Weiwei Xing, Yue Cheng, Hongzhu Yi et al.
PRISM: Reducing Spurious Implicit Biases in Vision-Language Models with LLM-Guided Embedding Projection
Mahdiyar Molahasani, Azadeh Motamedi, Michael Greenspan et al.
Rethinking Fair Representation Learning for Performance-Sensitive Tasks
Charles Jones, Fabio De Sousa Ribeiro, Mélanie Roschewitz et al.
SEBRA : Debiasing through Self-Guided Bias Ranking
Adarsh Kappiyath, Abhra Chaudhuri, AJAY JAISWAL et al.
Thumb on the Scale: Optimal Loss Weighting in Last Layer Retraining
Nathan Stromberg, Christos Thrampoulidis, Lalitha Sankar
Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation
Rohith Peddi, Saurabh ., Ayush Abhay Shrivastava et al.
Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
Yuancheng Xu, Chenghao Deng, Yanchao Sun et al.
Constructing Concept-based Models to Mitigate Spurious Correlations with Minimal Human Effort
Jeeyung Kim, Ze Wang, Qiang Qiu
Discovering and Mitigating Visual Biases through Keyword Explanation
Younghyun Kim, Sangwoo Mo, Minkyu Kim et al.
Discovering Bias in Latent Space: An Unsupervised Debiasing Approach
Dyah Adila, Shuai Zhang, Boran Han et al.
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning
Weilin Chen, Ruichu Cai, Zeqin Yang et al.
FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization
Cheng Yang, Jixi Liu, Yunhe Yan et al.
From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions
Trenton Chang, Jenna Wiens
From Fake to Real: Pretraining on Balanced Synthetic Images to Prevent Spurious Correlations in Image Recognition
Maan Qraitem, Kate Saenko, Bryan Plummer
Generalizing Orthogonalization for Models with Non-Linearities
David Rügamer, Chris Kolb, Tobias Weber et al.
ViG-Bias: Visually Grounded Bias Discovery and Mitigation
Badr-Eddine Marani, Mohamed HANINI, Nihitha Malayarukil et al.