Shiqi Wang

According to our database, Shiqi Wang authored at least 39 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Code-Aware Prompting: A Study of Coverage-Guided Test Generation in Regression Setting using LLM.

Gabriel Ryan, Siddhartha Jain, Mingyue Shang, Shiqi Wang, Xiaofei Ma, Murali Krishna Ramanathan, Baishakhi Ray

Proc. ACM Softw. Eng., 2024

Horizon-Length Prediction: Advancing Fill-in-the-Middle Capabilities for Code Generation with Lookahead Planning.

Yifeng Ding, Hantian Ding, Shiqi Wang, Qing Sun, Varun Kumar, Zijian Wang

CoRR, 2024

Training LLMs to Better Self-Debug and Explain Code.

Nan Jiang, Xiaopeng Li, Shiqi Wang, Qiang Zhou, Soneya Binta Hossain, Baishakhi Ray, Varun Kumar, Xiaofei Ma, Anoop Deoras

CoRR, 2024

Token Alignment via Character Matching for Subword Completion.

Ben Athiwaratkun, Shiqi Wang, Mingyue Shang, Yuchen Tian, Zijian Wang, Sujan Kumar Gonugondla, Sanjay Krishna Gouda, Rob Kwiatkowski, Ramesh Nallapati, Bing Xiang

CoRR, 2024

ReTA: Recursively Thinking Ahead to Improve the Strategic Reasoning of Large Language Models.

Jinhao Duan, Shiqi Wang, James Diffenderfer, Lichao Sun, Tianlong Chen, Bhavya Kailkhura, Kaidi Xu

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Reasoning and Planning with Large Language Models in Code Development.

Hao Ding, Ziwei Fan, Ingo Gühring, Gaurav Gupta, Wooseok Ha, Jun Huan, Linbo Liu, Behrooz Omidvar-Tehrani, Shiqi Wang, Hao Zhou

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

CodeFort: Robust Training for Code Generation Models.

Yuhao Zhang, Shiqi Wang, Haifeng Qian, Zijian Wang, Mingyue Shang, Linbo Liu, Sanjay Krishna Gouda, Baishakhi Ray, Murali Krishna Ramanathan, Xiaofei Ma, Anoop Deoras

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models.

Jinhao Duan, Hao Cheng, Shiqi Wang, Alex Zavalny, Chenan Wang, Renjing Xu, Bhavya Kailkhura, Kaidi Xu

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Token Alignment via Character Matching for Subword Completion.

Ben Athiwaratkun, Shiqi Wang, Mingyue Shang, Yuchen Tian, Zijian Wang, Sujan Kumar Gonugondla, Sanjay Krishna Gouda, Robert Kwiatkowski, Ramesh Nallapati, Parminder Bhatia, Bing Xiang

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Shifting Attention to Relevance: Towards the Uncertainty Estimation of Large Language Models.

Jinhao Duan, Hao Cheng, Shiqi Wang, Chenan Wang, Alex Zavalny, Renjing Xu, Bhavya Kailkhura, Kaidi Xu

CoRR, 2023

Greener yet Powerful: Taming Large Code Generation Models with Quantization.

Xiaokai Wei, Sujan K. Gonugondla, Wasi Uddin Ahmad, Shiqi Wang, Baishakhi Ray, Haifeng Qian, Xiaopeng Li, Varun Kumar, Zijian Wang, Yuchen Tian, Qing Sun, Ben Athiwaratkun, Mingyue Shang, Murali Krishna Ramanathan, Parminder Bhatia, Bing Xiang

CoRR, 2023

Towards Greener Yet Powerful Code Generation via Quantization: An Empirical Study.

Xiaokai Wei, Sujan Kumar Gonugondla, Shiqi Wang, Wasi Uddin Ahmad, Baishakhi Ray, Haifeng Qian, Xiaopeng Li, Varun Kumar, Zijian Wang, Yuchen Tian, Qing Sun, Ben Athiwaratkun, Mingyue Shang, Murali Krishna Ramanathan, Parminder Bhatia, Bing Xiang

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

Are Diffusion Models Vulnerable to Membership Inference Attacks?

Jinhao Duan, Fei Kong, Shiqi Wang, Xiaoshuang Shi, Kaidi Xu

Proceedings of the International Conference on Machine Learning, 2023

Multi-lingual Evaluation of Code Generation Models.

Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian, Ming Tan, Wasi Uddin Ahmad, Shiqi Wang, Qing Sun, Mingyue Shang, Sujan Kumar Gonugondla, Hantian Ding, Varun Kumar, Nathan Fulton, Arash Farahani, Siddhartha Jain, Robert Giaquinto, Haifeng Qian, Murali Krishna Ramanathan, Ramesh Nallapati

Proceedings of the Eleventh International Conference on Learning Representations, 2023

ReCode: Robustness Evaluation of Code Generation Models.

Shiqi Wang, Zheng Li, Haifeng Qian, Chenghao Yang, Zijian Wang, Mingyue Shang, Varun Kumar, Samson Tan, Baishakhi Ray, Parminder Bhatia, Ramesh Nallapati, Murali Krishna Ramanathan, Dan Roth, Bing Xiang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Efficient Neural Network Verification Using Branch and Bound

Shiqi Wang

PhD thesis, 2022

Multi-lingual Evaluation of Code Generation Models.

Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian, Ming Tan, Wasi Uddin Ahmad, Shiqi Wang, Qing Sun, Mingyue Shang, Sujan Kumar Gonugondla, Hantian Ding, Varun Kumar, Nathan Fulton, Arash Farahani, Siddhartha Jain, Robert Giaquinto, Haifeng Qian, Murali Krishna Ramanathan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta, Dan Roth, Bing Xiang

CoRR, 2022

General Cutting Planes for Bound-Propagation-Based Neural Network Verification.

Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks.

Huan Zhang, Shiqi Wang, Kaidi Xu, Yihan Wang, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter

Proceedings of the International Conference on Machine Learning, 2022

2021

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Verification.

Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter

CoRR, 2021

Cost-Aware Robust Tree Ensembles for Security Applications.

Yizheng Chen, Shiqi Wang, Weifan Jiang, Asaf Cidon, Suman Jana

Proceedings of the 30th USENIX Security Symposium, 2021

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification.

Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers.

Kaidi Xu, Huan Zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Security Classifiers with Verified Global Robustness Properties.

Yizheng Chen, Shiqi Wang, Yue Qin, Xiaojing Liao, Suman Jana, David A. Wagner

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Adaptive Verifiable Training Using Pairwise Class Similarity.

Shiqi Wang, Kevin Eykholt, Taesung Lee, Jiyong Jang, Ian M. Molloy

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Towards Understanding Fast Adversarial Training.

Bai Li, Shiqi Wang, Suman Jana, Lawrence Carin

CoRR, 2020

Towards Practical Lottery Ticket Hypothesis for Adversarial Training.

Bai Li, Shiqi Wang, Yunhan Jia, Yantao Lu, Zhenyu Zhong, Lawrence Carin, Suman Jana

CoRR, 2020

On Pruning Adversarially Robust Neural Networks.

Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana

CoRR, 2020

On Training Robust PDF Malware Classifiers.

Yizheng Chen, Shiqi Wang, Dongdong She, Suman Jana

Proceedings of the 29th USENIX Security Symposium, 2020

HYDRA: Pruning Adversarially Robust Neural Networks.

Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Bringing Engineering Rigor to Deep Learning.

Kexin Pei, Shiqi Wang, Yuchi Tian, Justin Whitehouse, Carl Vondrick, Yinzhi Cao, Baishakhi Ray, Suman Jana, Junfeng Yang

ACM SIGOPS Oper. Syst. Rev., 2019

Training Robust Tree Ensembles for Security.

Yizheng Chen, Shiqi Wang, Weifan Jiang, Asaf Cidon, Suman Jana

CoRR, 2019

Towards Compact and Robust Deep Neural Networks.

Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana

CoRR, 2019

Enhancing Gradient-based Attacks with Symbolic Intervals.

Shiqi Wang, Yizheng Chen, Ahmed Abdou, Suman Jana

CoRR, 2019

2018

Prediction of a hotspot pattern in keyword search results.

Jie Gao, Axinia Radeva, Chuyao Shen, Shiqi Wang, Qianbo Wang, Rebecca J. Passonneau

Comput. Speech Lang., 2018

MixTrain: Scalable Training of Formally Robust Neural Networks.

Shiqi Wang, Yizheng Chen, Ahmed Abdou, Suman Jana

CoRR, 2018

Formal Security Analysis of Neural Networks using Symbolic Intervals.

Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana

Proceedings of the 27th USENIX Security Symposium, 2018

Efficient Formal Safety Analysis of Neural Networks.

Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

ContexloT: Towards Providing Contextual Integrity to Appified IoT Platforms.

Yunhan Jack Jia, Qi Alfred Chen, Shiqi Wang, Amir Rahmati, Earlence Fernandes, Zhuoqing Morley Mao, Atul Prakash

Proceedings of the 24th Annual Network and Distributed System Security Symposium, 2017