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[Call for Papers] I am co-organizing the Workshop on Security and Safety in Machine Learning Systems at ICLR 2021. Please submit your paper here!
Compositional Generalization via Neural-Symbolic Stack Machines
Xinyun Chen, Chen Liang, Adams Wei Yu, Dawn Song, Denny Zhou.
Advances in Neural Information Processing Systems (NeurIPS), 2020.
Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis
Kavi Gupta, Peter Ebert Christensen*, Xinyun Chen*, Dawn Song. (* Equal contribution)
Advances in Neural Information Processing Systems (NeurIPS), 2020.
Spatiotemporal Attacks for Embodied Agents
Aishan Liu, Tairan Huang, Xianglong Liu, Yitao Xu, Yuqing Ma, Xinyun Chen, Stephen Maybank, Dacheng Tao.
European Conference on Computer Vision (ECCV), 2020.
Classifying Perturbation Types for Robustness Against Multiple Adversarial Perturbations
Pratyush Maini, Xinyun Chen, Bo Li, Dawn Song.
ICML Workshop on Uncertainty and Robustness in Deep Learning, 2020.
Xinyun Chen, Chen Liang, Adams Wei Yu, Denny Zhou, Dawn Song, Quoc V. Le.
International Conference on Learning Representations (ICLR), 2020. (Spotlight)
Deep Symbolic Superoptimization Without Human Knowledge
Hui Shi, Yang Zhang, Xinyun Chen, Yuandong Tian, Jishen Zhao.
International Conference on Learning Representations (ICLR), 2020.
Learning to Perform Local Rewriting for Combinatorial Optimization
Xinyun Chen, Yuandong Tian.
Advances in Neural Information Processing Systems (NeurIPS), 2019.
Coda: An End-to-End Neural Program Decompiler
Cheng Fu, Huili Chen, Haolan Liu, Xinyun Chen, Yuandong Tian, Farinaz Koushanfar, Jishen Zhao.
Advances in Neural Information Processing Systems (NeurIPS), 2019.
REFIT: a Unified Watermark Removal Framework for Deep Learning Systems with Limited Data
Xinyun Chen*, Wenxiao Wang*, Chris Bender, Yiming Ding, Ruoxi Jia, Bo Li, Dawn Song. (* Equal contribution)
Early version in ICML Workshop on Security and Privacy, 2019.
Execution-Guided Neural Program Synthesis
Xinyun Chen, Chang Liu, Dawn Song.
International Conference on Learning Representations (ICLR), 2019.
Tree-to-tree Neural Networks for Program Translation
Xinyun Chen, Chang Liu, Dawn Song.
Advances in Neural Information Processing Systems (NeurIPS), 2018.
Fooling Vision and Language Models Despite Localization and Attention Mechanism
Xiaojun Xu, Xinyun Chen, Chang Liu, Anna Rohrbach, Trevor Darrell, Dawn Song.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Towards Synthesizing Complex Programs from Input-Output Examples
Xinyun Chen, Chang Liu, Dawn Song.
International Conference on Learning Representations (ICLR), 2018.
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, Dawn Song.
Media coverage: Motherboard | The Register
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong
Warren He, James Wei, Xinyun Chen, Nicholas Carlini, Dawn Song.
USENIX Workshop on Offensive Technologies (WOOT), 2017.
Delving into Transferable Adversarial Examples and Black-box Attacks
Yanpei Liu, Xinyun Chen, Chang Liu, and Dawn Song.
International Conference on Learning Representations (ICLR), 2017.
A General Retraining Framework for Scalable Adversarial Classification
Bo Li, Yevgeniy Vorobeychik, Xinyun Chen.
NeurIPS Workshop on Adversarial Training, 2016.
Latent Attention For If-Then Program Synthesis
Xinyun Chen, Chang Liu, Richard Shin, Dawn Song, Mingcheng Chen.
Advances in Neural Information Processing Systems (NeurIPS), 2016.
Rising Stars in EECS, 2020.
Facebook Fellowship, 2020.
Departmental Fellowship of EECS, UC Berkeley, 2017.
The Prize of Excellent Bachelor Thesis (top 1% in Shanghai Jiao Tong University), 2017.
Outstanding Graduate of Shanghai Jiao Tong University, 2017.
Gold Medal of Asia-Pacific Informatics Olympiad in China District, 2012.
Silver Medal of Chinese Team Selection Contest, 2012.
Aug 2017 - Present: Ph.D., Computer Science, UC Berkeley. Advisor: Prof. Dawn Song.
Sep 2013 - Jun 2017: B.S., ACM Honored Class, Zhiyuan College, Shanghai Jiao Tong University. Rank: 1/30.
Dec 2020: Deep Learning for Program Synthesis from Input-Output Examples, NeurIPS Workshop on Computer-Assisted Programming.
June 2020: Neural Program Synthesis for Navigation and Language Understanding, CVPR Tutorial on Neuro-Symbolic Visual Reasoning and Program Synthesis.
April 2020: Learning to Perform Local Rewriting for Combinatorial Optimization, Google.
Feb 2020: Neural-Symbolic Reader for Reading Comprehension, Google, Mountain View.
Jan 2020: Learning to Perform Local Rewriting in Discrete Search Spaces, Alibaba Group, Sunnyvale.
Oct 2019: Neural Program Synthesis from Natural Language Specification, Open Virtual Assistant Lab, Stanford University.
Feb 2019: Neural Program Synthesis from Input-Output Examples, UC San Diego.
Nov 2018: Towards Synthesizing Complex Programs from Input-Output Examples, guest lecture in CS294-157: Deep Learning and Program Synthesis.
Oct 2018: Neural Program Synthesis from Input-Output Examples, Facebook Big Code Summit.
May 2018: Deep Learning for Program Synthesis, guest lecture in CS379C: Computational Models of the Neocortex, Stanford University.
Co-organizer of the Workshop on Security and Safety in Machine Learning Systems at ICLR 2021.
Co-organizer of the Workshop on Adversarial Machine Learning in Real-World Computer Vision Systems and Online Challenges at CVPR 2021.
Co-organizer of the Workshop on Adversarial Machine Learning in Computer Vision at CVPR 2020.
Program Committee / Reviewer of: IJCAI (senior PC in 2021), NeurIPS (top 10% reviewers in 2020), ICLR, ICML, AAAI, ACL, EMNLP, NAACL, ECCV, IJCV, TIFS, TDSC.
Graduate Student Instructor of CS 188: Introduction to Artificial Intelligence, Spring 2021, UC Berkeley.
In my spare time, I enjoy listening to all kinds of music. I have played the piano since kindergarten, and received the highest-level certificates of piano and music theory in China. I used to play some other instruments, including recorder and harmonica.