Subgroups Matter for Robust Bias Mitigation
Fuente:
arXiv
Saved in:
| Main Authors: | Alloula, Anissa, Jones, Charles, Glocker, Ben, Papież, Bartłomiej W. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Representation Invariance and Allocation: When Subgroup Balance Matters
by: Alloula, Anissa, et al.
Published: (2025)
by: Alloula, Anissa, et al.
Published: (2025)
On Biases in a UK Biobank-based Retinal Image Classification Model
by: Alloula, Anissa, et al.
Published: (2024)
by: Alloula, Anissa, et al.
Published: (2024)
Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST
by: Wu, Fuping, et al.
Published: (2025)
by: Wu, Fuping, et al.
Published: (2025)
Autopet Challenge 2023: nnUNet-based whole-body 3D PET-CT Tumour Segmentation
by: Alloula, Anissa, et al.
Published: (2023)
by: Alloula, Anissa, et al.
Published: (2023)
Bias Detection via Maximum Subgroup Discrepancy
by: Němeček, Jiří, et al.
Published: (2025)
by: Němeček, Jiří, et al.
Published: (2025)
Deep Neural Networks for Predicting Recurrence and Survival in Patients with Esophageal Cancer After Surgery
by: Zheng, Yuhan, et al.
Published: (2024)
by: Zheng, Yuhan, et al.
Published: (2024)
A Primer on Causal and Statistical Dataset Biases for Fair and Robust Image Analysis
by: Jones, Charles, et al.
Published: (2025)
by: Jones, Charles, et al.
Published: (2025)
Counterfactual Identifiability via Dynamic Optimal Transport
by: Ribeiro, Fabio De Sousa, et al.
Published: (2025)
by: Ribeiro, Fabio De Sousa, et al.
Published: (2025)
Adversarial Robustness of VAEs across Intersectional Subgroups
by: Ramanaik, Chethan Krishnamurthy, et al.
Published: (2024)
by: Ramanaik, Chethan Krishnamurthy, et al.
Published: (2024)
Causal Representation Learning with Observational Grouping for CXR Classification
by: Rasal, Rajat, et al.
Published: (2025)
by: Rasal, Rajat, et al.
Published: (2025)
Bias Fitting to Mitigate Length Bias of Reward Model in RLHF
by: Zhao, Kangwen, et al.
Published: (2025)
by: Zhao, Kangwen, et al.
Published: (2025)
Flow Stochastic Segmentation Networks
by: Ribeiro, Fabio De Sousa, et al.
Published: (2025)
by: Ribeiro, Fabio De Sousa, et al.
Published: (2025)
Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs
by: Siddique, Zara, et al.
Published: (2025)
by: Siddique, Zara, et al.
Published: (2025)
Efficient Bias Mitigation Without Privileged Information
by: Zarlenga, Mateo Espinosa, et al.
Published: (2024)
by: Zarlenga, Mateo Espinosa, et al.
Published: (2024)
Object-Centric Neuro-Argumentative Learning
by: Jacob, Abdul Rahman, et al.
Published: (2025)
by: Jacob, Abdul Rahman, et al.
Published: (2025)
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
by: Kori, Avinash, et al.
Published: (2024)
by: Kori, Avinash, et al.
Published: (2024)
Whither Bias Goes, I Will Go: An Integrative, Systematic Review of Algorithmic Bias Mitigation
by: Hickman, Louis, et al.
Published: (2024)
by: Hickman, Louis, et al.
Published: (2024)
Mitigating Participation Imbalance Bias in Asynchronous Federated Learning
by: Chang, Xiangyu, et al.
Published: (2025)
by: Chang, Xiangyu, et al.
Published: (2025)
Adaptive Repetition for Mitigating Position Bias in LLM-Based Ranking
by: Vardasbi, Ali, et al.
Published: (2025)
by: Vardasbi, Ali, et al.
Published: (2025)
Measuring and Mitigating Bias for Tabular Datasets with Multiple Protected Attributes
by: Duong, Manh Khoi, et al.
Published: (2024)
by: Duong, Manh Khoi, et al.
Published: (2024)
From Garbage to Gold: A Data-Architectural Theory of Predictive Robustness
by: John, Terrence J. Lee-St., et al.
Published: (2026)
by: John, Terrence J. Lee-St., et al.
Published: (2026)
Mitigating Estimation Bias with Representation Learning in TD Error-Driven Regularization
by: Chen, Haohui, et al.
Published: (2025)
by: Chen, Haohui, et al.
Published: (2025)
Indirect Attention: Turning Context Misalignment into a Feature
by: Bahaduri, Bissmella, et al.
Published: (2025)
by: Bahaduri, Bissmella, et al.
Published: (2025)
ProbLog4Fairness: A Neurosymbolic Approach to Modeling and Mitigating Bias
by: Adriaensen, Rik, et al.
Published: (2025)
by: Adriaensen, Rik, et al.
Published: (2025)
Fisher-Guided Selective Forgetting: Mitigating The Primacy Bias in Deep Reinforcement Learning
by: Falzari, Massimiliano, et al.
Published: (2025)
by: Falzari, Massimiliano, et al.
Published: (2025)
Backdoor for Debias: Mitigating Model Bias with Backdoor Attack-based Artificial Bias
by: Wu, Shangxi, et al.
Published: (2023)
by: Wu, Shangxi, et al.
Published: (2023)
Does Order Matter : Connecting The Law of Robustness to Robust Generalization
by: Mandal, Himadri, et al.
Published: (2026)
by: Mandal, Himadri, et al.
Published: (2026)
Mitigating Exposure Bias in Score-Based Generation of Molecular Conformations
by: Wang, Sijia, et al.
Published: (2024)
by: Wang, Sijia, et al.
Published: (2024)
Mitigating the Structural Bias in Graph Adversarial Defenses
by: Fang, Junyuan, et al.
Published: (2025)
by: Fang, Junyuan, et al.
Published: (2025)
Identification and Mitigating Bias in Quantum Machine Learning
by: Swaminathan, Nandhini, et al.
Published: (2024)
by: Swaminathan, Nandhini, et al.
Published: (2024)
Understanding and Mitigating Tokenization Bias in Language Models
by: Phan, Buu, et al.
Published: (2024)
by: Phan, Buu, et al.
Published: (2024)
Age Predictors Through the Lens of Generalization, Bias Mitigation, and Interpretability: Reflections on Causal Implications
by: Paul, Debdas, et al.
Published: (2026)
by: Paul, Debdas, et al.
Published: (2026)
ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups
by: Hu, Jingyu, et al.
Published: (2024)
by: Hu, Jingyu, et al.
Published: (2024)
ConQuER: Modular Architectures for Control and Bias Mitigation in IQP Quantum Generative Models
by: Zou, Xiaocheng, et al.
Published: (2025)
by: Zou, Xiaocheng, et al.
Published: (2025)
Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention
by: Hoang, Van Thuy, et al.
Published: (2025)
by: Hoang, Van Thuy, et al.
Published: (2025)
Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning
by: Tepeli, Yasin I., et al.
Published: (2024)
by: Tepeli, Yasin I., et al.
Published: (2024)
Robust Graph Condensation via Classification Complexity Mitigation
by: Luo, Jiayi, et al.
Published: (2025)
by: Luo, Jiayi, et al.
Published: (2025)
Quantifying and Mitigating Self-Preference Bias of LLM Judges
by: Yang, Jinming, et al.
Published: (2026)
by: Yang, Jinming, et al.
Published: (2026)
Mitigating Extrinsic Gender Bias for Bangla Classification Tasks
by: Joy, Sajib Kumar Saha, et al.
Published: (2024)
by: Joy, Sajib Kumar Saha, et al.
Published: (2024)
Mitigating Bias in Dataset Distillation
by: Cui, Justin, et al.
Published: (2024)
by: Cui, Justin, et al.
Published: (2024)
Similar Items
-
Representation Invariance and Allocation: When Subgroup Balance Matters
by: Alloula, Anissa, et al.
Published: (2025) -
On Biases in a UK Biobank-based Retinal Image Classification Model
by: Alloula, Anissa, et al.
Published: (2024) -
Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST
by: Wu, Fuping, et al.
Published: (2025) -
Autopet Challenge 2023: nnUNet-based whole-body 3D PET-CT Tumour Segmentation
by: Alloula, Anissa, et al.
Published: (2023) -
Bias Detection via Maximum Subgroup Discrepancy
by: Němeček, Jiří, et al.
Published: (2025)