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Chen Chen

9 papers here

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

author position
  • first author2
  • middle author7

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CV5
  • cs.LG3
  • cs.CR1
ORCID 0000-0002-3525-9755
same name
  • Chen Chen — 42 papers, h 45
  • Chen Chen — 30 papers, h 19
  • Chen Chen — 30 papers, h 10
  • Chen Chen — 28 papers, h 14
  • Chen Chen — 24 papers, h 26
  • Chen Chen — 22 papers, h 11

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
20202023
most citedCalFAT: Calibrated Federated Adversarial Training with Label Skewness

15 citations · 23 across the 9 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CV2023

DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models

Zhenting Wang, Chen Chen, Lingjuan Lyu +2

Recent text-to-image diffusion models have shown surprising performance in generating high-quality images. However, concerns have arisen regarding the unauthorized data usage durin…

cs.CV2023

Alteration-free and Model-agnostic Origin Attribution of Generated Images

Zhenting Wang, Chen Chen, Yi Zeng +2

Recently, there has been a growing attention in image generation models. However, concerns have emerged regarding potential misuse and intellectual property (IP) infringement assoc…

cs.LG2023★ 2 cited

Towards Adversarially Robust Continual Learning

Tao Bai, Chen Chen, Lingjuan Lyu +2

Recent studies show that models trained by continual learning can achieve the comparable performances as the standard supervised learning and the learning flexibility of continual…

cs.LG2023★ 4 cited

Delving into the Adversarial Robustness of Federated Learning

Jie Zhang, Bo Li, Chen Chen +4

In Federated Learning (FL), models are as fragile as centrally trained models against adversarial examples. However, the adversarial robustness of federated learning remains largel…

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