Light-weight Fine-tuning Method for Defending Adversarial Noise in Pre-trained Medical Vision-Language Models

Light-weight Fine-tuning Method for Defending Adversarial Noise in Pre-trained Medical Vision-Language Models

2 July 2024

Xuezhe Ma

Papers citing "Light-weight Fine-tuning Method for Defending Adversarial Noise in Pre-trained Medical Vision-Language Models"

6 / 6 papers shown

Title
BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs Sheng Zhang Yanbo Xu Naoto Usuyama Hanwen Xu J. Bagga ... Carlo Bifulco M. Lungren Tristan Naumann Sheng Wang Hoifung Poon LM&MA MedIm 151 191 0 10 Jan 2025
Progressive Compositionality in Text-to-Image Generative Models Xu Han Linghao Jin Xiaofeng Liu Paul Pu Liang CoGe 93 2 0 22 Oct 2024
Guided Diffusion Model for Adversarial Purification Jinyi Wang Zhaoyang Lyu Dahua Lin Bo Dai Hongfei Fu DiffM 180 77 0 30 May 2022
Tightening the Approximation Error of Adversarial Risk with Auto Loss Function Search Pengfei Xia Ziqiang Li Bin Li AAML 32 3 0 09 Nov 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,735 0 24 Feb 2021
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao B. Wen Qian Wang AAML 71 467 0 02 Feb 2021