1.3k citations · 1.9k across the 14 of their papers we have counts for
15 papers
zkFuzz: Foundation and Framework for Effective Fuzzing of Zero-Knowledge Circuits
Hideaki Takahashi, Jihwan Kim, Suman Jana +1
Zero-knowledge (ZK) circuits enable privacy-preserving computations and are central to many cryptographic protocols. Systems like Circom simplify ZK development by combining witnes…
SmartInv: Multimodal Learning for Smart Contract Invariant Inference
Sally Junsong Wang, Kexin Pei, Junfeng Yang
Smart contracts are software programs that enable diverse business activities on the blockchain. Recent research has identified new classes of "machine un-auditable" bugs that aris…
Detecting Buggy Contracts via Smart Testing
Sally Junsong Wang, Jianan Yao, Kexin Pei +2
Smart contracts are susceptible to critical vulnerabilities. Hybrid dynamic analyses, such as concolic execution assisted fuzzing and foundation model assisted fuzzing, have emerge…
Comment on Revisiting Neural Program Smoothing for Fuzzing
Dongdong She, Kexin Pei, Junfeng Yang +2
MLFuzz, a work accepted at ACM FSE 2023, revisits the performance of a machine learning-based fuzzer, NEUZZ. We demonstrate that its main conclusion is entirely wrong due to severa…
Exploiting Code Symmetries for Learning Program Semantics
Kexin Pei, Weichen Li, Qirui Jin +5
This paper tackles the challenge of teaching code semantics to Large Language Models (LLMs) for program analysis by incorporating code symmetries into the model architecture. We in…
Development of a Neural Network-Based Mathematical Operation Protocol for Embedded Hexadecimal Digits Using Neural Architecture Search (NAS)
Victor Robila, Kexin Pei, Junfeng Yang
It is beneficial to develop an efficient machine-learning based method for addition using embedded hexadecimal digits. Through a comparison between human-developed machine learning…