2 papers
cs.CV2025
TAB: Transformer Attention Bottlenecks enable User Intervention and Debugging in Vision-Language Models
Pooyan Rahmanzadehgervi, Hung Huy Nguyen, Rosanne Liu +2
Multi-head self-attention (MHSA) is a key component of Transformers, a widely popular architecture in both language and vision. Multiple heads intuitively enable different parallel…
cs.LG2025
Logit Scaling for Out-of-Distribution Detection
Andrija Djurisic, Rosanne Liu, Mladen Nikolic
The safe deployment of machine learning and AI models in open-world settings hinges critically on the ability to detect out-of-distribution (OOD) data accurately, data samples that…