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Feng Liu

12 papers hereh-index 6111 citations13 works total

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

author position
  • middle author5
  • last author7

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • cs.CV5
same name
  • Feng Liu — 156 papers, h 7
  • Feng Liu — 92 papers
  • Feng Liu — 77 papers, h 62
  • Feng Liu — 76 papers, h 48
  • Feng Liu — 38 papers, h 48
  • Feng Liu — 35 papers, h 4

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
20242026
most citedVisual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models

3 citations · 5 across the 11 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CV2025

Sample-Specific Noise Injection For Diffusion-Based Adversarial Purification

Yuhao Sun, Jiacheng Zhang, Zesheng Ye +2

Diffusion-based purification (DBP) methods aim to remove adversarial noise from the input sample by first injecting Gaussian noise through a forward diffusion process, and then rec…

cs.LG2025

Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction

Zesheng Ye, Chengyi Cai, Ruijiang Dong +4

As large-scale pre-trained foundation models continue to expand in size and capability, efficiently adapting them to specific downstream tasks has become increasingly critical. Des…

cs.LG2025

Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts

Chengyi Cai, Zesheng Ye, Lei Feng +2

Model reprogramming adapts pretrained models to downstream tasks by modifying only the input and output spaces. Visual reprogramming (VR) is one instance for vision tasks that adds…

cs.CV2025

Attribute-based Visual Reprogramming for Vision-Language Models

Chengyi Cai, Zesheng Ye, Lei Feng +2

Visual reprogramming (VR) reuses pre-trained vision models for downstream image classification tasks by adding trainable noise patterns to inputs. When applied to vision-language m…

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