Kexin Pei

According to our database1, Kexin Pei authored at least 25 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
TRACED: Execution-aware Pre-training for Source Code.
Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

2023
Learning Approximate Execution Semantics From Traces for Binary Function Similarity.
IEEE Trans. Software Eng., April, 2023

SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
CoRR, 2023

Symmetry-Preserving Program Representations for Learning Code Semantics.
CoRR, 2023

TraceFixer: Execution Trace-Driven Program Repair.
CoRR, 2023

Can Large Language Models Reason about Program Invariants?
Proceedings of the International Conference on Machine Learning, 2023

2022
Development of a Neural Network-Based Mathematical Operation Protocol for Embedded Hexadecimal Digits Using Neural Architecture Search (NAS).
CoRR, 2022

NeuDep: neural binary memory dependence analysis.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

SymLM: Predicting Function Names in Stripped Binaries via Context-Sensitive Execution-Aware Code Embeddings.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021
StateFormer: fine-grained type recovery from binaries using generative state modeling.
Proceedings of the ESEC/FSE '21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021

XDA: Accurate, Robust Disassembly with Transfer Learning.
Proceedings of the 28th Annual Network and Distributed System Security Symposium, 2021

2020
Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity.
CoRR, 2020

2019
Bringing Engineering Rigor to Deep Learning.
ACM SIGOPS Oper. Syst. Rev., 2019

NEUZZ: Efficient Fuzzing with Neural Program Smoothing.
Proceedings of the 2019 IEEE Symposium on Security and Privacy, 2019

2018
DeepXplore: Automated Whitebox Testing of Deep Learning Systems.
GetMobile Mob. Comput. Commun., 2018

NEUZZ: Efficient Fuzzing with Neural Program Learning.
CoRR, 2018

Formal Security Analysis of Neural Networks using Symbolic Intervals.
Proceedings of the 27th USENIX Security Symposium, 2018

Efficient Formal Safety Analysis of Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

DeepTest: automated testing of deep-neural-network-driven autonomous cars.
Proceedings of the 40th International Conference on Software Engineering, 2018

2017
Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems.
CoRR, 2017

HVLearn: Automated Black-Box Analysis of Hostname Verification in SSL/TLS Implementations.
Proceedings of the 2017 IEEE Symposium on Security and Privacy, 2017

2016
Python probabilistic type inference with natural language support.
Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering, 2016

HERCULE: attack story reconstruction via community discovery on correlated log graph.
Proceedings of the 32nd Annual Conference on Computer Security Applications, 2016

2015
LEAPS: Detecting Camouflaged Attacks with Statistical Learning Guided by Program Analysis.
Proceedings of the 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2015

2014
Private search on key-value stores with hierarchical indexes.
Proceedings of the IEEE 30th International Conference on Data Engineering, Chicago, 2014


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