2 papers
cs.CV2025
ASCENT-ViT: Attention-based Scale-aware Concept Learning Framework for Enhanced Alignment in Vision Transformers
Sanchit Sinha, Guangzhi Xiong, Aidong Zhang
As Vision Transformers (ViTs) are increasingly adopted in sensitive vision applications, there is a growing demand for improved interpretability. This has led to efforts to forward…
cs.LG2024
ProtoNAM: Prototypical Neural Additive Models for Interpretable Deep Tabular Learning
Guangzhi Xiong, Sanchit Sinha, Aidong Zhang
Generalized additive models (GAMs) have long been a powerful white-box tool for the intelligible analysis of tabular data, revealing the influence of each feature on the model pred…