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ORCIDYao Qin 0001
Person information
- affiliation: University of California Santa Barbara, Department of Electrical and Computer Engineering, CA, USA
- affiliation (PhD): University of California San Diego, CA, USA
Other persons with the same name
- Yao Qin — disambiguation page
- Yao Qin 0002
![[0000-0002-3777-6334]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-3777-6334")
— Northwesten Institute of Nuclear Technology, Xi'an, China (and 1 more)
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Books and Theses
- 2020
[b1]Yao Qin:
Detecting, Diagnosing, Deflecting and Designing Adversarial Attacks. University of California, San Diego, USA, 2020
Journal Articles
- 2018
- [j1]Yao Qin, Mengyang Feng, Huchuan Lu, Garrison W. Cottrell:
Hierarchical Cellular Automata for Visual Saliency. Int. J. Comput. Vis. 126(7): 751-770 (2018)
Conference and Workshop Papers
- 2024
- [c14]Bhagyashree Puranik, Ahmad Beirami, Yao Qin, Upamanyu Madhow:
Improving Robustness via Tilted Exponential Layer: A Communication-Theoretic Perspective. AISTATS 2024: 4510-4518 - 2023
- [c13]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed H. Chi, Jilin Chen, Alex Beutel:
Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. EMNLP (Findings) 2023: 127-139 - [c12]Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin:
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data. NeurIPS 2023 - [c11]Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel:
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. SaTML 2023: 365-376 - 2022
- [c10]Jindong Gu, Volker Tresp, Yao Qin:
Are Vision Transformers Robust to Patch Perturbations? ECCV (12) 2022: 404-421 - [c9]Jieyu Zhao, Xuezhi Wang, Yao Qin, Jilin Chen, Kai-Wei Chang:
Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers. EMNLP (Findings) 2022: 1634-1640 - [c8]Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang:
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. NeurIPS 2022 - 2021
- [c7]Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi:
Improving Calibration through the Relationship with Adversarial Robustness. NeurIPS 2021: 14358-14369 - 2020
- [c6]Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi:
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. EMNLP (1) 2020: 5141-5146 - [c5]Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton:
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions. ICLR 2020 - 2019
- [c4]Yao Qin, Nicholas Carlini, Garrison W. Cottrell, Ian J. Goodfellow, Colin Raffel:
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition. ICML 2019: 5231-5240 - 2018
- [c3]Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya V. Nori:
Autofocus Layer for Semantic Segmentation. MICCAI (3) 2018: 603-611 - 2017
- [c2]Yao Qin, Dongjin Song, Haifeng Chen, Wei Cheng, Guofei Jiang, Garrison W. Cottrell:
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction. IJCAI 2017: 2627-2633 - 2015
- [c1]Yao Qin, Huchuan Lu, Yiqun Xu, He Wang:
Saliency detection via Cellular Automata. CVPR 2015: 110-119
Informal and Other Publications
- 2023
- [i23]Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin:
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data. CoRR abs/2302.01381 (2023) - [i22]Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel:
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. CoRR abs/2302.11188 (2023) - [i21]Shaila Niazi, Navid Anjum Aadit, Masoud Mohseni, Shuvro Chowdhury, Yao Qin, Kerem Yunus Camsari:
Training Deep Boltzmann Networks with Sparse Ising Machines. CoRR abs/2303.10728 (2023) - [i20]Jindong Gu, Ahmad Beirami, Xuezhi Wang, Alex Beutel, Philip H. S. Torr, Yao Qin:
Towards Robust Prompts on Vision-Language Models. CoRR abs/2304.08479 (2023) - [i19]Xinlu Zhang, Shiyang Li, Xianjun Yang, Chenxin Tian, Yao Qin, Linda Ruth Petzold:
Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting. CoRR abs/2305.12723 (2023) - [i18]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel:
Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. CoRR abs/2305.13535 (2023) - [i17]Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, Philip H. S. Torr:
A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models. CoRR abs/2307.12980 (2023) - [i16]Ananth Balashankar, Xiao Ma, Aradhana Sinha, Ahmad Beirami, Yao Qin, Jilin Chen, Alex Beutel:
Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning. CoRR abs/2310.16959 (2023) - [i15]Bhagyashree Puranik, Ahmad Beirami, Yao Qin, Upamanyu Madhow:
Improving Robustness via Tilted Exponential Layer: A Communication-Theoretic Perspective. CoRR abs/2311.01047 (2023) - [i14]Litian Liu, Yao Qin:
Detecting Out-of-Distribution Through the Lens of Neural Collapse. CoRR abs/2311.01479 (2023) - [i13]Andong Hua, Jindong Gu, Zhiyu Xue, Nicholas Carlini, Eric Wong, Yao Qin:
Initialization Matters for Adversarial Transfer Learning. CoRR abs/2312.05716 (2023) - [i12]Litian Liu, Yao Qin:
Fast Decision Boundary based Out-of-Distribution Detector. CoRR abs/2312.11536 (2023) - 2022
- [i11]Jieyu Zhao, Xuezhi Wang, Yao Qin, Jilin Chen, Kai-Wei Chang:
Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers. CoRR abs/2210.16298 (2022) - 2021
- [i10]Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang:
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. CoRR abs/2110.07858 (2021) - [i9]Jindong Gu, Volker Tresp, Yao Qin:
Are Vision Transformers Robust to Patch Perturbations? CoRR abs/2111.10659 (2021) - 2020
- [i8]Yao Qin, Nicholas Frosst, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton:
Deflecting Adversarial Attacks. CoRR abs/2002.07405 (2020) - [i7]Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi:
Improving Uncertainty Estimates through the Relationship with Adversarial Robustness. CoRR abs/2006.16375 (2020) - [i6]Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi:
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. CoRR abs/2010.02338 (2020) - 2019
- [i5]Yao Qin, Nicholas Carlini, Ian J. Goodfellow, Garrison W. Cottrell, Colin Raffel:
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition. CoRR abs/1903.10346 (2019) - [i4]Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton:
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions. CoRR abs/1907.02957 (2019) - 2018
- [i3]Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya V. Nori:
Autofocus Layer for Semantic Segmentation. CoRR abs/1805.08403 (2018) - 2017
- [i2]Yao Qin, Dongjin Song, Haifeng Chen, Wei Cheng, Guofei Jiang, Garrison W. Cottrell:
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction. CoRR abs/1704.02971 (2017) - [i1]Yao Qin, Mengyang Feng, Huchuan Lu, Garrison W. Cottrell:
Hierarchical Cellular Automata for Visual Saliency. CoRR abs/1705.09425 (2017)
Coauthor Index
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