29 citations · 57 across the 11 of their papers we have counts for
11 papers
Glovity: Learning Dexterous Contact-Rich Manipulation via Spatial Wrench Feedback Teleoperation System
Yuyang Gao, Haofei Ma, Pai Zheng
We present Glovity, a novel, low-cost wearable teleoperation system that integrates a spatial wrench (force-torque) feedback device with a haptic glove featuring fingertip Hall sen…
DUE: Dynamic Uncertainty-Aware Explanation Supervision via 3D Imputation
Qilong Zhao, Yifei Zhang, Mengdan Zhu +4
Explanation supervision aims to enhance deep learning models by integrating additional signals to guide the generation of model explanations, showcasing notable improvements in bot…
3DPFIX: Improving Remote Novices' 3D Printing Troubleshooting through Human-AI Collaboration
Nahyun Kwon, Tong Sun, Yuyang Gao +4
The widespread consumer-grade 3D printers and learning resources online enable novices to self-train in remote settings. While troubleshooting plays an essential part of 3D printin…
Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations
Tong Steven Sun, Yuyang Gao, Shubham Khaladkar +4
The local explanation provides heatmaps on images to explain how Convolutional Neural Networks (CNNs) derive their output. Due to its visual straightforwardness, the method has bee…
Saliency-Augmented Memory Completion for Continual Learning
Guangji Bai, Chen Ling, Yuyang Gao +1
Continual Learning is considered a key step toward next-generation Artificial Intelligence. Among various methods, replay-based approaches that maintain and replay a small episodic…
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning
Yuyang Gao, Siyi Gu, Junji Jiang +3
As the societal impact of Deep Neural Networks (DNNs) grows, the goals for advancing DNNs become more complex and diverse, ranging from improving a conventional model accuracy metr…
RES: A Robust Framework for Guiding Visual Explanation
Yuyang Gao, Tong Steven Sun, Guangji Bai +3
Despite the fast progress of explanation techniques in modern Deep Neural Networks (DNNs) where the main focus is handling "how to generate the explanations", advanced research que…
Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment
Yuyang Gao, Tong Sun, Liang Zhao +1
While Deep Neural Networks (DNNs) are deriving the major innovations in nearly every field through their powerful automation, we are also witnessing the peril behind automation as…
Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning
Yuyang Gao, Giorgio A. Ascoli, Liang Zhao
Continual learning is considered a promising step towards next-generation Artificial Intelligence (AI), where deep neural networks (DNNs) make decisions by continuously learning a…
BEAN: Interpretable Representation Learning with Biologically-Enhanced Artificial Neuronal Assembly Regularization
Yuyang Gao, Giorgio A. Ascoli, Liang Zhao
Deep neural networks (DNNs) are known for extracting useful information from large amounts of data. However, the representations learned in DNNs are typically hard to interpret, es…
DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums
Yuyang Gao, Lingfei Wu, Houman Homayoun +1
Online health communities such as the online breast cancer forum enable patients (i.e., users) to interact and help each other within various subforums, which are subsections of th…