Nathan Jacobs

Causality for Inherently Explainable Transformers: CAT-XPLAIN

2022 · arXiv (Cornell University)

There have been several post-hoc explanation approaches developed to explain pre-trained black-box neural networks. However, there is still a gap in research efforts toward designing neural networks that are inherently explainable. In this paper, we …

Vision-Language Pseudo-Labels for Single-Positive Multi-Label Learning

2023 · arXiv (Cornell University)

This paper presents a novel approach to Single-Positive Multi-label Learning. In general multi-label learning, a model learns to predict multiple labels or categories for a single input image. This is in contrast with standard multi-class …