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Yang Zhang

4 papers hereh-index 5106 citations27 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CR3
  • cs.SE1
same name
  • Yang Zhang — 51 papers, h 85
  • Yang Zhang — 51 papers, h 15
  • Yang Zhang — 47 papers, h 28
  • Yang Zhang — 45 papers, h 18
  • Yang Zhang — 44 papers, h 42
  • Yang Zhang — 41 papers, h 24

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192025
most citedTea: Program Repair Using Neural Network Based on Program Information Attention Matrix

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CR2025

Psyzkaller: Learning from Historical and On-the-Fly Execution Data for Smarter Seed Generation in OS kernel Fuzzing

Boyu Liu, Yang Zhang, Liang Cheng +6

OS Kernel fuzzers such as Syzkaller often struggle to generate syscall sequences that respect intrinsic Syscall Dependency Relations (SDRs), resulting in seeds that either violate…

cs.CR2025

Automatic Generation of a Cryptography Misuse Taxonomy Using Large Language Models

Yang Zhang, Wenyi Ouyang, Yi Zhang +3

The prevalence of cryptographic API misuse (CAM) is compromising the effectiveness of cryptography and in turn the security of modern systems and applications. Despite extensive ef…

cs.SE2021★ 1 cited

Tea: Program Repair Using Neural Network Based on Program Information Attention Matrix

Wenshuo Wang, Chen Wu, Liang Cheng +1

The advance in machine learning (ML)-driven natural language process (NLP) points a promising direction for automatic bug fixing for software programs, as fixing a buggy program ca…

cs.CR2019

Optimizing seed inputs in fuzzing with machine learning

Liang Cheng, Yang Zhang, Yi Zhang +4

The success of a fuzzing campaign is heavily depending on the quality of seed inputs used for test generation. It is however challenging to compose a corpus of seed inputs that ena…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.