3 papers
cs.AI2026
ForEx: A Formal Verification Framework for Explainable Reasoning in Logical Fallacy Detection and Annotation
Pei-Cing Huang, Chienyu Liu, Chan Hsu +3
Current evaluations of Large Language Models (LLMs) on logical fallacy detection focus on predicted labels, but do not establish whether those labels are supported by the reasoning…
cs.LG2024
Subgroup Analysis via Model-based Rule Forest
I-Ling Cheng, Chan Hsu, Chantung Ku +2
Machine learning models are often criticized for their black-box nature, raising concerns about their applicability in critical decision-making scenarios. Consequently, there is a…
stat.ML2019
Towards Interpretable Deep Extreme Multi-label Learning
Yihuang Kang, I-Ling Cheng, Wenjui Mao +2
Many Machine Learning algorithms, such as deep neural networks, have long been criticized for being "black-boxes"-a kind of models unable to provide how it arrive at a decision wit…