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Peng Cheng

6 papers hereh-index 7232 citations10 works total

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

author position
  • middle author6

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CR4
  • cs.CV1
  • cs.LG1
same name
  • Peng Cheng — 26 papers, h 40
  • Peng Cheng — 24 papers, h 22
  • Peng Cheng — 17 papers, h 15
  • Peng Cheng — 11 papers, h 56
  • Peng Cheng — 11 papers, h 4
  • Peng Cheng — 11 papers, h 2

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
20202025
most citedTrojanZoo: Towards Unified, Holistic, and Practical Evaluation of Neural Backdoors

20 citations · 53 across the 6 of their papers we have counts for

collaborators
Showing cs.CRShow all

4 papers · 1 filter

cs.CR2025

A Survey of Operating System Kernel Fuzzing

Jiacheng Xu, He Sun, Shihao Jiang +8

The Operating System (OS) kernel is foundational in modern computing, especially with the proliferation of diverse computing devices. However, its development also comes with vulne…

cs.CR2024★ 10 cited

SoK: Dataset Copyright Auditing in Machine Learning Systems

Linkang Du, Xuanru Zhou, Min Chen +5

As the implementation of machine learning (ML) systems becomes more widespread, especially with the introduction of larger ML models, we perceive a spring demand for massive data.…

cs.CR2023★ 8 cited

ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning

Linkang Du, Min Chen, Mingyang Sun +4

Data is a critical asset in AI, as high-quality datasets can significantly improve the performance of machine learning models. In safety-critical domains such as autonomous vehicle…

cs.CR2022★ 15 cited

VeriFi: Towards Verifiable Federated Unlearning

Xiangshan Gao, Xingjun Ma, Jingyi Wang +5

Federated learning (FL) is a collaborative learning paradigm where participants jointly train a powerful model without sharing their private data. One desirable property for FL is…

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