Shiyu Chang is an Assistant Professor at UC Santa Barbara, where his research centers on machine learning with applications in natural language processing and computer vision.
Before joining UC Santa Barbara, Shiyu was a research scientist at the MIT-IBM Watson AI Lab, where he worked closely with Prof. Regina Barzilay and Prof. Tommi Jaakkola. He earned both his B.S. and Ph.D. from the University of Illinois at Urbana-Champaign. His Ph.D. advisor is Prof. Thomas S. Huang.
Guanyu Yao ( 2024 - )
Jingbo Yang ( 2024 - )
Li An ( 2024 - )
Xinyi Gao ( 2024 - )
Jiabao Ji ( 2022 - )
Yujian Liu ( 2022 - )
Qiucheng Wu ( 2021 - )
Bairu Hou ( 2021 - )
Guanhua Zhang ( 2021 - 2023 ): now Ph.D. at Max Planck Institute for Intelligent Systems
Jiajun Wang ( 2023 )
Chris Riney ( 2023 - )
Edwin Yee ( 2022 - )
Yifan Ke ( 2023 )
Liliana Nguyen ( 2022 - 2023 )
Shamita Gurusu ( 2022 - 2023 )
Hugo Lin ( 2022 - 2023 )
Wesley Truong ( 2022 - 2023 )
Zhiyuan Ren ( 2021 - 2022 )
Full publications on Google Scholar.
‡ indicates authors with equal contribution. ☆ indicates my students or interns.
Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference
Jiabao Ji☆, Yujian Liu☆, Yang Zhang, Gaowen Liu, Ramana Rao Kompella, Sijia Liu, Shiyu Chang
NeurIPS'24: Advances in Neural Information Processing Systems
Revisiting Who's Harry Potter: Towards Targeted Unlearning from a Causal Intervention Perspective
Yujian Liu☆, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang
EMNLP'24: Conference on Empirical Methods in Natural Language Processing
Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing
Jiabao Ji☆ ‡, Bairu Hou☆ ‡, Alexander Robey‡, George J. Pappas, Hamed Hassani, Yang Zhang, Eric Wong, Shiyu Chang
ArXiv Preprint
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling
Bairu Hou☆ Yujian Liu☆, Kaizhi Qian, Jacob Andreas, Shiyu Chang, Yang Zhang
ICML'24: International Conference on Machine Learning
Advancing the Robustness of Large Language Models through Self-Denoised Smoothing
Jiabao Ji☆ ‡, Bairu Hou☆ ‡, Zhen Zhang‡, Guanhua Zhang☆ ‡, Wenqi Fan, Qing Li, Yang Zhang, Gaowen Liu, Sijia Liu, Shiyu Chang
NAACL'24: Annual Conference of the North American Chapter of the Association for Computational Linguistics
Correcting Diffusion Generation through Resampling
Yujian Liu☆, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang
CVPR'24: IEEE Computer Vision and Pattern Recognition
Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference
Jiabao Ji☆, Yujian Liu☆, Yang Zhang, Gaowen Liu, Ramana Rao Kompella, Sijia Liu, Shiyu Chang
NeurIPS'24: Advances in Neural Information Processing Systems
Revisiting Who's Harry Potter: Towards Targeted Unlearning from a Causal Intervention Perspective
Yujian Liu☆, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang
EMNLP'24: Conference on Empirical Methods in Natural Language Processing
Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing
Jiabao Ji☆ ‡, Bairu Hou☆ ‡, Alexander Robey‡, George J. Pappas, Hamed Hassani, Yang Zhang, Eric Wong, Shiyu Chang
ArXiv Preprint
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling
Bairu Hou☆ Yujian Liu☆, Kaizhi Qian, Jacob Andreas, Shiyu Chang, Yang Zhang
ICML'24: International Conference on Machine Learning
Advancing the Robustness of Large Language Models through Self-Denoised Smoothing
Jiabao Ji☆ ‡, Bairu Hou☆ ‡, Zhen Zhang‡, Guanhua Zhang☆ ‡, Wenqi Fan, Qing Li, Yang Zhang, Gaowen Liu, Sijia Liu, Shiyu Chang
NAACL'24: Annual Conference of the North American Chapter of the Association for Computational Linguistics
Correcting Diffusion Generation through Resampling
Yujian Liu☆, Yang Zhang, Tommi S. Jaakkola, Shiyu Chang
CVPR'24: IEEE Computer Vision and Pattern Recognition
Improving Diffusion Models for Scene Text Editing with Dual Encoders
Jiabao Ji☆ ‡, Guanhua Zhang☆ ‡, Zhaowen Wang, Bairu Hou, Zhifei Zhang, Brian Price, Shiyu Chang
TMLR'24: Transactions on Machine Learning Research
Harnessing the Spatial-Temporal Attention of Diffusion Models for High-Fidelity Text-to-Image Synthesis
Qiucheng Wu☆ ‡, Yujian Liu☆ ‡, Handong Zhao, Trung Bui, Zhe Lin, Yang Zhang, Shiyu Chang
ICCV'23: International Conference on Computer Vision
Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models
Guanhua Zhang☆ ‡, Jiabao Ji☆ ‡, Yang Zhang, Mo Yu, Tommi S. Jaakkola, Shiyu Chang
ICML'23: International Conference on Machine Learning
PromptBoosting: Black-Box Text Classification with Ten Forward Passes
Bairu Hou☆, Joe O'Connor, Jacob Andreas, Shiyu Chang, Yang Zhang
ICML'23: International Conference on Machine Learning
Uncovering the Disentanglement Capability in Text-to-Image Diffusion Models
Qiucheng Wu☆, Yujian Liu☆, Handong Zhao, Ajinkya Kale, Trung Bui, Tong Yu, Zhe Lin, Yang Zhang, Shiyu Chang
CVPR'23: IEEE Computer Vision and Pattern Recognition
TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization
Bairu Hou☆, Jinghan Jia‡, Yihua Zhang‡, Guanhua Zhang☆ ‡, Yang Zhang, Sijia Liu, Shiyu Chang
ICLR'23: International Conference on Learning Representations
Fairness Reprogramming
Guanhua Zhang☆ ‡, Yihua Zhang‡, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang
NeurIPS'22: Advances in Neural Information Processing Systems
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization
Yihua Zhang‡, Guanhua Zhang☆ ‡, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu
ICML'22: International Conference on Machine Learning
Learning Stable Classifiers by Transferring Unstable Features
Yujia Bao, Shiyu Chang, Regina Barzilay
ICML'22: International Conference on Machine Learning
ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers
Kaizhi Qian‡, Yang Zhang‡, Heting Gao, Junru Ni, Cheng-I Lai, David Cox, Mark A. Hasegawa-Johnson, Shiyu Chang
ICML'22: International Conference on Machine Learning
Data-Efficient Double-Win Lottery Tickets from Robust Pre-training
Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang
ICML'22: International Conference on Machine Learning
Linearity Grafting: How Neuron Pruning Helps Certifiable Robustness
Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang
ICML'22: International Conference on Machine Learning
DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings
Yung-Sung Chuang, Rumen Dangovski, Hongyin Luo, Yang Zhang, Shiyu Chang, Marin Soljačić, Shang-Wen Li, Wen-tau Yih, Yoon Kim, James Glass
NAACL'22: Annual Conference of the North American Chapter of the Association for Computational Linguistics
Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free
Tianlong Chen‡, Zhenyu Zhang‡, Yihua Zhang‡, Shiyu Chang, Sijia Liu, Zhangyang Wang
CVPR'22: IEEE Computer Vision and Pattern Recognition
Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding
Sijia Wang, Mo Yu, Shiyu Chang, Lichao Sun, Lifu Huang
ACL-Finding'22: Annual Meeting of the Association for Computational Linguistics
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu
ICLR'22: International Conference on Learning Representations
Adversarial Support Alignment
Shangyuan Tong☆ ‡, Timur Garipov‡, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola
ICLR'22: International Conference on Learning Representations
Optimizer Amalgamation
Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang
ICLR'22: International Conference on Learning Representations
Understanding Interlocking Dynamics of Cooperative Rationalization
Mo Yu‡, Yang Zhang‡, Shiyu Chang‡, Tommi S. Jaakkola
NeurIPS'21: Advances in Neural Information Processing Systems
TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up
Yifan Jiang, Shiyu Chang, Zhangyang Wang
NeurIPS'21: Advances in Neural Information Processing Systems
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition
Cheng-I Lai, Yang Zhang, Alexander Liu, Shiyu Chang, Yi-Lun Liao, Yung-Sung Chuang, Kaizhi Qian, Sameer Khurana, David Cox, James Glass
NeurIPS'21: Advances in Neural Information Processing Systems
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
ICML'21: International Conference on Machine Learning
The Lottery Ticket Hypothesis for Pre-trained BERT Networks
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin
NeurIPS'20: Advances in Neural Information Processing Systems
Invariant Rationalization
Shiyu Chang‡, Yang Zhang‡, Mo Yu‡, Tommi S. Jaakkola
ICML'20: International Conference on Machine Learning
Unsupervised Speech Decomposition via Triple Information Bottleneck
Kaizhi Qian‡, Yang Zhang‡, Shiyu Chang, David Cox, Mark A. Hasegawa-Johnson
ICML'20: International Conference on Machine Learning
Few-shot Text Classification with Distributional Signatures
Yujia Bao☆ ‡, Menghua Wu☆ ‡, Shiyu Chang, Regina Barzilay
ICLR'20: International Conference on Learning Representations
A Game Theoretic Approach to Class-wise Selective Rationalization
Shiyu Chang‡, Yang Zhang‡, Mo Yu‡, Tommi S. Jaakkola
NeurIPS'19: Advances in Neural Information Processing Systems
A Stratified Approach to Robustness for Randomly Smoothed Classifiers
Guang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola
NeurIPS'19: Advances in Neural Information Processing Systems
Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control
Mo Yu‡, Shiyu Chang‡, Yang Zhang‡, Tommi S. Jaakkola
EMNLP'19: Conference on Empirical Methods in Natural Language Processing
AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
Kaizhi Qian‡, Yang Zhang‡, Shiyu Chang, Xuesong Yang, Mark A. Hasegawa-Johnson
ICML'19: International Conference on Machine Learning
Deriving Machine Attention from Human Rationales
Yujia Bao☆, Shiyu Chang, Mo Yu, Regina Barzilay
EMNLP'18: Conference on Empirical Methods in Natural Language Processing
Image Super-Resolution via Dual-State Recurrent Networks
Wei Han☆ ‡, Shiyu Chang‡, Ding Liu, Mo Yu, Michael Witbrock, Thomas S. Huang
CVPR'18: IEEE Computer Vision and Pattern Recognition
Dilated Recurrent Neural Networks
Shiyu Chang‡, Yang Zhang‡, Wei Han‡, Mo Yu, Xiaoxiao Guo, Wei Tan, Xiaodong Cui, Michael Witbrock, Mark A. Hasegawa-Johnson, Thomas S. Huang
NIPS'17: Advances in Neural Information Processing Systems
Streaming Recommender Systems
Shiyu Chang, Yang Zhang, Jiliang Tang, Dawei Yin, Yi Chang, Mark A. Hasegawa-Johnson, Thomas S. Huang
WWW'17: ACM International World Wide Web Conference
Positive-Unlabeled Learning in Streaming Networks
Shiyu Chang‡, Yang Zhang‡, Jiliang Tang, Dawei Yin, Yi Chang, Mark A. Hasegawa-Johnson, Thomas S. Huang
KDD'16: ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Heterogeneous Network Embedding via Deep Architectures
Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang
KDD'15: ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Factorized Similarity Learning in Networks
Shiyu Chang, Guo-Jun Qi, Charu C. Aggarwal, Jiayu Zhou, Meng Wang, Thomas S. Huang
ICDM'14: IEEE International Conference on Data Mining
Learning Locally-Adaptive Decision Functions for Person Verification
Zhen Li, Shiyu Chang, Feng Liang, Thomas S. Huang, Liangliang Cao, John R. Smith
CVPR'13: IEEE Computer Vision and Pattern Recognition
CS 165B: Introduction to Machine Learning ( F'21, F'22, W'24 )
CS 190I: Introduction to Deep Learning ( F'23, F'24 )
CS 291A: Special Topics on Adversarial Machine Learning ( W'22, W'23 )
- Some words keep me moving forward:
"A job well done is its own reward. You take pride in the things you do, not for others to see, not for the respect, or glory, or any other rewards it might bring. You take pride in what you do, because you're doing your best. If you believe in something, you stick with it. When things get difficult, you try harder."
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