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Yiming Li

10 papers hereh-index 171k citations28 works total

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

author position
  • first author1
  • middle author7

Across the 8 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CR4
  • cs.CV4
  • cs.CL1
  • cs.LG1
same name
  • Yiming Li — 21 papers, h 9
  • Yiming Li — 16 papers, h 16
  • Yiming Li — 14 papers, h 24
  • Yiming Li — 14 papers, h 4
  • Yiming Li — 14 papers, h 8
  • Yiming Li — 13 papers, h 8

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 citedBackdoor Attack in the Physical World

36 citations · 46 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025

Towards Dataset Copyright Evasion Attack against Personalized Text-to-Image Diffusion Models

Kuofeng Gao, Yufei Zhu, Yiming Li +4

Text-to-image (T2I) diffusion models enable high-quality image generation conditioned on textual prompts. However, fine-tuning these pre-trained models for personalization raises c…

cs.CV2024

Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision Transformers

Sheng Yang, Jiawang Bai, Kuofeng Gao +3

Given the power of vision transformers, a new learning paradigm, pre-training and then prompting, makes it more efficient and effective to address downstream visual recognition tas…

cs.CV2023★ 5 cited

Domain Watermark: Effective and Harmless Dataset Copyright Protection is Closed at Hand

Junfeng Guo, Yiming Li, Lixu Wang +4

The prosperity of deep neural networks (DNNs) is largely benefited from open-source datasets, based on which users can evaluate and improve their methods. In this paper, we revisit…

cs.CV2021★ 5 cited

Regional Adversarial Training for Better Robust Generalization

Chuanbiao Song, Yanbo Fan, Yichen Yang +4

Adversarial training (AT) has been demonstrated as one of the most promising defense methods against various adversarial attacks. To our knowledge, existing AT-based methods usuall…

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