[
abstract
+]
Preprint
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Xianglin Yang, Jin Song Dong.
Exploring the Evolution of Hidden Activations with Live-Update Visualization.
2024 .
2023
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Xianglin Yang, Yun Lin, Yifan Zhang, Linpeng Huang, Jin Song Dong, Hong Mei.
DeepDebugger: An Interactive Time-Travelling Debugging Approach for Deep Classifiers.
ESEC/FSE 2023 .
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Tianyuan Jin, Xianglin Yang, Xiaokui Xiao, Pan Xu.
Thompson Sampling with Less Exploration is Fast and Optimal.
ICML 2023 .
2022
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Ruofan Liu, Yun Lin, Xianglin Yang, Jin Song Dong.
Debugging and Explaining Metric Learning Approaches: An Influence Function Based Perspective.
NeurIPS 2022 .
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Xianglin Yang, Yun Lin, Ruofan Liu, Jin Song Dong.
Temporality Spatialization: A Scalable and Faithful Time-Travelling Visualization for Deep Classifier Training.
IJCAI 2022 .
[code]
[website]
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Ruofan Liu, Yun Lin, Xianglin Yang, Siang Hwee Ng, Dinil Mon Divakaran, Jin Song Dong.
Inferring Phishing Intention via Webpage Appearance and Dynamics: A Deep Vision Based Approach.
USENIX Security 2022 .
[code]
[website]
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Xianglin Yang#, Yun Lin#, Ruofan Liu, Zhenfeng He, Chao Wang, Jin Song Dong, and Hong Mei.
DeepVisualInsight: Time-Travelling Visualization for Spatio-Temporal Causality of Deep Classification Training.
AAAI 2022. [oral presentation, 4.5%].
[paper]
[video]
[code]
[website]