Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models

1 code implementation • 29 Nov 2024 • Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang

Fine-tuning foundation models often compromises their robustness to distribution shifts.

A Causal Framework to Unify Common Domain Generalization Approaches

no code implementations • 13 Jul 2023 • Nevin L. Zhang, Kaican Li, Han Gao, Weiyan Xie, Zhi Lin, Zhenguo Li, Luning Wang, Yongxiang Huang

Domain generalization (DG) is about learning models that generalize well to new domains that are related to, but different from, the training domain(s).

Domain Generalization

Two-Stage Holistic and Contrastive Explanation of Image Classification

1 code implementation • 10 Jun 2023 • Weiyan Xie, Xiao-Hui Li, Zhi Lin, Leonard K. M. Poon, Caleb Chen Cao, Nevin L. Zhang

The need to explain the output of a deep neural network classifier is now widely recognized.

Classification Image Classification

Consistency Regularization for Domain Generalization with Logit Attribution Matching

1 code implementation • 13 May 2023 • Han Gao, Kaican Li, Weiyan Xie, Zhi Lin, Yongxiang Huang, Luning Wang, Caleb Chen Cao, Nevin L. Zhang

In this paper, we consider a third, lesser-known setting where a training domain is endowed with a collection of pairs of examples that share the same semantic information.

Data Augmentation Domain Generalization

ViT-CX: Causal Explanation of Vision Transformers

1 code implementation • 6 Nov 2022 • Weiyan Xie, Xiao-Hui Li, Caleb Chen Cao, Nevin L. Zhang

Despite the popularity of Vision Transformers (ViTs) and eXplainable AI (XAI), only a few explanation methods have been designed specially for ViTs thus far.

Explainable Artificial Intelligence (XAI)

Example Perplexity

1 code implementation • 16 Mar 2022 • Nevin L. Zhang, Weiyan Xie, Zhi Lin, Guanfang Dong, Xiao-Hui Li, Caleb Chen Cao, Yunpeng Wang

Some examples are easier for humans to classify than others.