#bias mitigation
16 papers · 1 filter
Fairness Pruning: Locating Demographic Bias in GLU-MLP Layers via Differential Activations
Pere Martra, Eugenio MartÃnez Cámara, Alfonso Ureña López
The paper introduces Fairness Pruning, a method that identifies and zeroes a small set of neurons in GLU-MLP layers of large language models to locate and modulate demographic bias…
Scaling Vision-Language Models Is Not Enough to Mitigate Bias
Ioannis Sarridis, Ioannis Kompatsiaris, Symeon Papadopoulos
The paper empirically evaluates 194 vision‑language models to see how model size, training data, and architecture affect bias, finding that larger models do not consistently reduce…
MedXplore: Towards Reliable and Unbiased Generalized Category Discovery in Medical Imaging
Jianwei He, Kailin Lyu, Junhao Dong +6
The paper presents MedXplore, a unified framework for generalized category discovery in medical imaging that leverages frequency-domain adaptive attention and an adaptive cosine-an…
TPCD: Tone-Pressure Contrastive Decoding and the Label-Free Gating Bottleneck in Vision-Language Models
Jinkun Zhao, Kui Zhang, Wenjun Wu
The paper introduces Tone‑Pressure Contrastive Decoding (TPCD), which subtracts logits from high‑pressure prompts from those of neutral prompts to reduce commitment bias in vision‑…
Demographically-Conditioned Synthetic Medical Images for Bias Mitigation and Bias Detection in Disease Classifiers
Mahmoud Ibrahim, Bart Elen, Chang Sun +2
The paper proposes using a demographically-conditioned synthetic image generator to both improve fairness in training medical image classifiers and to provide more reliable bias de…
Can We Steer the Black-Box? Towards Controllability-Centric Evaluation of Recommender Systems with Collaborative Agents
Jiwen Zhou, Xiang Liu, Mingming Li +5
The paper introduces CtrlBench-Rec, a collaborative multi‑agent framework for evaluating how controllable recommender systems are, focusing on tasks such as target content discover…