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Journal Articles
- 2023
[j4]Kexin Pei
, Zhou Xuan, Junfeng Yang, Suman Jana, Baishakhi Ray:
Learning Approximate Execution Semantics From Traces for Binary Function Similarity. IEEE Trans. Software Eng. 49(4): 2776-2790 (2023)- 2019
- [j3]Kexin Pei, Yinzhi Cao, Junfeng Yang, Suman Jana:
DeepXplore: automated whitebox testing of deep learning systems. Commun. ACM 62(11): 137-145 (2019) - [j2]Kexin Pei, Shiqi Wang, Yuchi Tian, Justin Whitehouse, Carl Vondrick, Yinzhi Cao, Baishakhi Ray, Suman Jana, Junfeng Yang:
Bringing Engineering Rigor to Deep Learning. ACM SIGOPS Oper. Syst. Rev. 53(1): 59-67 (2019) - 2018
- [j1]Kexin Pei, Yinzhi Cao, Junfeng Yang, Suman Jana:
DeepXplore: Automated Whitebox Testing of Deep Learning Systems. GetMobile Mob. Comput. Commun. 22(3): 36-38 (2018)
Conference and Workshop Papers
- 2024
- [c19]Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, Karthik R. Narasimhan:
SWE-bench: Can Language Models Resolve Real-world Github Issues? ICLR 2024 - [c18]Kexin Pei, Weichen Li, Qirui Jin, Shuyang Liu, Scott Geng, Lorenzo Cavallaro, Junfeng Yang, Suman Jana:
Exploiting Code Symmetries for Learning Program Semantics. ICML 2024 - [c17]Yangruibo Ding, Benjamin Steenhoek, Kexin Pei, Gail E. Kaiser, Wei Le, Baishakhi Ray:
TRACED: Execution-aware Pre-training for Source Code. ICSE 2024: 36:1-36:12 - [c16]Sally Junsong Wang, Kexin Pei, Junfeng Yang:
SmartInv: Multimodal Learning for Smart Contract Invariant Inference. SP 2024: 2217-2235 - 2023
- [c15]Kexin Pei, David Bieber, Kensen Shi, Charles Sutton, Pengcheng Yin:
Can Large Language Models Reason about Program Invariants? ICML 2023: 27496-27520 - 2022
- [c14]Xin Jin, Kexin Pei, Jun Yeon Won, Zhiqiang Lin:
SymLM: Predicting Function Names in Stripped Binaries via Context-Sensitive Execution-Aware Code Embeddings. CCS 2022: 1631-1645 - [c13]Kexin Pei, Dongdong She, Michael Wang, Scott Geng, Zhou Xuan, Yaniv David, Junfeng Yang, Suman Jana, Baishakhi Ray:
NeuDep: neural binary memory dependence analysis. ESEC/SIGSOFT FSE 2022: 747-759 - 2021
- [c12]Kexin Pei, Jonas Guan, David Williams-King, Junfeng Yang, Suman Jana:
XDA: Accurate, Robust Disassembly with Transfer Learning. NDSS 2021 - [c11]Kexin Pei, Jonas Guan, Matthew Broughton, Zhongtian Chen, Songchen Yao, David Williams-King, Vikas Ummadisetty, Junfeng Yang, Baishakhi Ray, Suman Jana:
StateFormer: fine-grained type recovery from binaries using generative state modeling. ESEC/SIGSOFT FSE 2021: 690-702 - 2019
- [c10]Dongdong She, Kexin Pei, Dave Epstein, Junfeng Yang, Baishakhi Ray, Suman Jana:
NEUZZ: Efficient Fuzzing with Neural Program Smoothing. IEEE Symposium on Security and Privacy 2019: 803-817 - 2018
- [c9]Yuchi Tian, Kexin Pei, Suman Jana, Baishakhi Ray:
DeepTest: automated testing of deep-neural-network-driven autonomous cars. ICSE 2018: 303-314 - [c8]Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana:
Efficient Formal Safety Analysis of Neural Networks. NeurIPS 2018: 6369-6379 - [c7]Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana:
Formal Security Analysis of Neural Networks using Symbolic Intervals. USENIX Security Symposium 2018: 1599-1614 - 2017
- [c6]Kexin Pei, Yinzhi Cao, Junfeng Yang, Suman Jana:
DeepXplore: Automated Whitebox Testing of Deep Learning Systems. SOSP 2017: 1-18 - [c5]Suphannee Sivakorn, George Argyros, Kexin Pei, Angelos D. Keromytis, Suman Jana:
HVLearn: Automated Black-Box Analysis of Hostname Verification in SSL/TLS Implementations. IEEE Symposium on Security and Privacy 2017: 521-538 - 2016
- [c4]Kexin Pei, Zhongshu Gu, Brendan Saltaformaggio, Shiqing Ma, Fei Wang, Zhiwei Zhang, Luo Si, Xiangyu Zhang, Dongyan Xu:
HERCULE: attack story reconstruction via community discovery on correlated log graph. ACSAC 2016: 583-595 - [c3]Zhaogui Xu, Xiangyu Zhang, Lin Chen, Kexin Pei, Baowen Xu:
Python probabilistic type inference with natural language support. SIGSOFT FSE 2016: 607-618 - 2015
- [c2]Zhongshu Gu, Kexin Pei, Qifan Wang, Luo Si, Xiangyu Zhang, Dongyan Xu:
LEAPS: Detecting Camouflaged Attacks with Statistical Learning Guided by Program Analysis. DSN 2015: 57-68 - 2014
- [c1]Haibo Hu, Jianliang Xu, Xizhong Xu, Kexin Pei, Byron Choi, Shuigeng Zhou:
Private search on key-value stores with hierarchical indexes. ICDE 2014: 628-639
Informal and Other Publications
- 2024
- [i16]Dongdong She, Kexin Pei, Junfeng Yang, Baishakhi Ray, Suman Jana:
Comment on Revisiting Neural Program Smoothing for Fuzzing. CoRR abs/2409.04504 (2024) - [i15]Sally Junsong Wang, Jianan Yao, Kexin Pei, Hidedaki Takahashi, Junfeng Yang:
Detecting Buggy Contracts via Smart Testing. CoRR abs/2409.04597 (2024) - 2023
- [i14]Islem Bouzenia, Yangruibo Ding, Kexin Pei, Baishakhi Ray, Michael Pradel:
TraceFixer: Execution Trace-Driven Program Repair. CoRR abs/2304.12743 (2023) - [i13]Yangruibo Ding, Benjamin Steenhoek, Kexin Pei, Gail E. Kaiser, Wei Le, Baishakhi Ray:
TRACED: Execution-aware Pre-training for Source Code. CoRR abs/2306.07487 (2023) - [i12]Kexin Pei, Weichen Li, Qirui Jin, Shuyang Liu, Scott Geng, Lorenzo Cavallaro, Junfeng Yang, Suman Jana:
Symmetry-Preserving Program Representations for Learning Code Semantics. CoRR abs/2308.03312 (2023) - [i11]Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, Karthik Narasimhan:
SWE-bench: Can Language Models Resolve Real-World GitHub Issues? CoRR abs/2310.06770 (2023) - 2022
- [i10]Kexin Pei, Dongdong She, Michael Wang, Scott Geng, Zhou Xuan, Yaniv David, Junfeng Yang, Suman Jana, Baishakhi Ray:
NeuDep: Neural Binary Memory Dependence Analysis. CoRR abs/2210.02853 (2022) - [i9]Victor Robila, Kexin Pei, Junfeng Yang:
Development of a Neural Network-Based Mathematical Operation Protocol for Embedded Hexadecimal Digits Using Neural Architecture Search (NAS). CoRR abs/2211.15416 (2022) - 2020
- [i8]Kexin Pei, Jonas Guan, David Williams-King, Junfeng Yang, Suman Jana:
XDA: Accurate, Robust Disassembly with Transfer Learning. CoRR abs/2010.00770 (2020) - [i7]Kexin Pei, Zhou Xuan, Junfeng Yang, Suman Jana, Baishakhi Ray:
Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity. CoRR abs/2012.08680 (2020) - 2018
- [i6]Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana:
Formal Security Analysis of Neural Networks using Symbolic Intervals. CoRR abs/1804.10829 (2018) - [i5]Dongdong She, Kexin Pei, Dave Epstein, Junfeng Yang, Baishakhi Ray, Suman Jana:
NEUZZ: Efficient Fuzzing with Neural Program Learning. CoRR abs/1807.05620 (2018) - [i4]Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana:
Efficient Formal Safety Analysis of Neural Networks. CoRR abs/1809.08098 (2018) - 2017
- [i3]Kexin Pei, Yinzhi Cao, Junfeng Yang, Suman Jana:
DeepXplore: Automated Whitebox Testing of Deep Learning Systems. CoRR abs/1705.06640 (2017) - [i2]Yuchi Tian, Kexin Pei, Suman Jana, Baishakhi Ray:
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars. CoRR abs/1708.08559 (2017) - [i1]Kexin Pei, Yinzhi Cao, Junfeng Yang, Suman Jana:
Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems. CoRR abs/1712.01785 (2017)
Coauthor Index
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