4 papers
Which Geometry on Which Layer? Measured Sign-Spectral Assignment in Mixed-Optimizer Training
Hiroki Naganuma, Laura Gomezjurado, Mahdi Ghaznavi +5
Modern neural-network training uses mixed recipes, assigning AdamW-like or sign-based updates to embedding and output layers and spectral updates to hidden matrices. These assignme…
Trained Models Tell Us How to Make Them Robust to Spurious Correlation without Group Annotation
Mahdi Ghaznavi, Hesam Asadollahzadeh, Fahimeh Hosseini Noohdani +5
Classifiers trained with Empirical Risk Minimization (ERM) tend to rely on attributes that have high spurious correlation with the target. This can degrade the performance on under…
GABInsight: Exploring Gender-Activity Binding Bias in Vision-Language Models
Ali Abdollahi, Mahdi Ghaznavi, Mohammad Reza Karimi Nejad +6
Vision-language models (VLMs) are intensively used in many downstream tasks, including those requiring assessments of individuals appearing in the images. While VLMs perform well i…
Annotation-Free Group Robustness via Loss-Based Resampling
Mahdi Ghaznavi, Hesam Asadollahzadeh, HamidReza Yaghoubi Araghi +3
It is well-known that training neural networks for image classification with empirical risk minimization (ERM) makes them vulnerable to relying on spurious attributes instead of ca…