8 citations · 25 across the 13 of their papers we have counts for
5 papers · 1 filter
Improving Users' Mental Model with Attention-directed Counterfactual Edits
Kamran Alipour, Arijit Ray, Xiao Lin +4
In the domain of Visual Question Answering (VQA), studies have shown improvement in users' mental model of the VQA system when they are exposed to examples of how these systems ans…
Trigger Hunting with a Topological Prior for Trojan Detection
Xiaoling Hu, Xiao Lin, Michael Cogswell +3
Despite their success and popularity, deep neural networks (DNNs) are vulnerable when facing backdoor attacks. This impedes their wider adoption, especially in mission critical app…
Confidence Calibration for Domain Generalization under Covariate Shift
Yunye Gong, Xiao Lin, Yi Yao +3
Existing calibration algorithms address the problem of covariate shift via unsupervised domain adaptation. However, these methods suffer from the following limitations: 1) they req…
Modular Adaptation for Cross-Domain Few-Shot Learning
Xiao Lin, Meng Ye, Yunye Gong +4
Adapting pre-trained representations has become the go-to recipe for learning new downstream tasks with limited examples. While literature has demonstrated great successes via repr…
Generating and Evaluating Explanations of Attended and Error-Inducing Input Regions for VQA Models
Arijit Ray, Michael Cogswell, Xiao Lin +4
Attention maps, a popular heatmap-based explanation method for Visual Question Answering (VQA), are supposed to help users understand the model by highlighting portions of the imag…