Adversarial Contrastive Learning

Adversarial contrastive learning (ACL) aims to improve the robustness and generalization of representation learning models by combining contrastive learning with adversarial training. Current research focuses on applying ACL to diverse data types, including graphs, time series, and images, often incorporating techniques like generative adversarial networks (GANs) or specific loss functions (e.g., InfoNCE) to enhance performance. This approach is particularly valuable in scenarios with limited labeled data or susceptibility to adversarial attacks, impacting fields like medical image analysis, fake news detection, and autonomous driving by creating more reliable and robust AI systems. The development of efficient ACL methods, such as coreset selection, is also a key area of investigation.

Papers

October 23, 2024

FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive Learning
Wei Chen, Meng Yuan, Zhao Zhang, Ruobing Xie, Fuzhen Zhuang, Deqing Wang, Rui Liu
LeArning Abstract Contrastive Learning Contrastive Objective Adversarial Contrastive Learning Recommendation Fairness Fairness Aware Recommendation Temporal Contrastive Graph

September 10, 2024

LAMP: Learnable Meta-Path Guided Adversarial Contrastive Learning for Heterogeneous Graphs
Siqing Li, Jin-Duk Park, Wei Huang, Xin Cao, Won-Yong Shin, Zhiqiang Xu
Contrastive Learning Heterogeneous Graph Adversarial Contrastive Learning Meta Path Heterogeneous Graph Contrastive

August 16, 2024

Adversarial Contrastive Learning Based Physics-Informed Temporal Networks for Cuffless Blood Pressure Estimation
Rui Wang, Mengshi Qi, Yingxia Shao, Anfu Zhou, Huadong Ma
Physic Informed Neural Network Time Varying Blood Pressure Temporal Variation Adversarial Contrastive Learning Physiological Time Series Data

August 9, 2024

Surgical-VQLA++: Adversarial Contrastive Learning for Calibrated Robust Visual Question-Localized Answering in Robotic Surgery
Long Bai, Guankun Wang, Mobarakol Islam, Lalithkumar Seenivasan, An Wang, Hongliang Ren
Medical Image Visual Question Answering Visual Question Robotic Surgery Adversarial Contrastive Learning Medical VQA Surgical Visual Question Answering

May 29, 2024

Contrastive-Adversarial and Diffusion: Exploring pre-training and fine-tuning strategies for sulcal identification
Michail Mamalakis, Héloïse de Vareilles, Shun-Chin Jim Wu, Ingrid Agartz, Lynn Egeland Mørch-Johnsen, Jane Garrison, Jon Simons, Pietro Lio, John Suckling, Graham Murray
Fine Tuning Pre Trained Diffusion Explainer General Strategy 3d CNN Fine Tuning Approach Adversarial Contrastive Learning Sulcal Graph

November 14, 2023

Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning
Shashank Kotyan, Danilo Vasconcellos Vargas
Adversarial Attack Native Robustness Adversarial Perturbation Object Detector Common Corruption Adversarial Contrastive Learning Adversarial Instance

August 1, 2023

Graph Contrastive Learning with Generative Adversarial Network
Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai
Graph Neural Network Generative Adversarial Network Adversarial Contrastive Learning

June 2, 2023

Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations
Dou Hu, Yinan Bao, Lingwei Wei, Wei Zhou, Songlin Hu
Emotion Recognition Community Conversation Structured Representation Adversarial Contrastive Learning Joint Contrastive Learning

April 30, 2023

Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan Kankanhalli
Adversarial Attack Adversarial Data Adversarial Contrastive Learning Adversarial Regularization

March 2, 2023

Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning
Rundong Luo, Yifei Wang, Yisen Wang
Data Augmentation Self Supervised Learning Adversarial Training Mixed Effect Adversarial Contrastive Learning Robustness Gap

February 21, 2023

Generalization Bounds for Adversarial Contrastive Learning
Xin Zou, Weiwei Liu
Adversarial Attack Adversarial Training Generalization Bound Adversarial Risk Adversarial Contrastive Learning

February 8, 2023

Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan Kankanhalli
Adversarial Attack COreset Selection Adversarial Contrastive Learning

October 11, 2022

Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks
Junfei Wu, Weizhi Xu, Qiang Liu, Shu Wu, Liang Wang
Graph Neural Network Fake News Detection Semantic Graph Adversarial Contrastive Learning Evidence Aware Fake News Detection

October 6, 2022

Adversarial Lagrangian Integrated Contrastive Embedding for Limited Size Datasets
Amin Jalali, Minho Lee
Augmentation Method Contrastive Training Adversarial Contrastive Learning Small Scale Datasets Adversarial Transfer

September 14, 2022

PointACL:Adversarial Contrastive Learning for Robust Point Clouds Representation under Adversarial Attack
Junxuan Huang, Yatong An, Lu cheng, Bai Chen, Junsong Yuan, Chunming Qiao
Adversarial Attack Adversarial Contrastive Learning 3D Adversarial Virtual Adversarial Training

July 22, 2022

Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness
Chaoning Zhang, Kang Zhang, Chenshuang Zhang, Axi Niu, Jiu Feng, Chang D. Yoo, In So Kweon
Adversarial Training Adversarial Robustness Robust Representation Robust Representation Learning Adversarial Contrastive Learning Adversarial Contrastive

July 18, 2022

Adversarial Contrastive Learning via Asymmetric InfoNCE
Qiying Yu, Jieming Lou, Xianyuan Zhan, Qizhang Li, Wangmeng Zuo, Yang Liu, Jingjing Liu
Contrastive Learning Adversarial Robustness Adversarial Perturbation Adversarial Learning Adversarial Sample Information Asymmetry Adversarial Contrastive Learning

April 21, 2022

Adversarial Contrastive Learning by Permuting Cluster Assignments
Muntasir Wahed, Afrina Tabassum, Ismini Lourentzou
Contrastive Learning Prototypical Contrastive Learning Adversarial Contrastive Learning Cluster Assignment

April 18, 2022

Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learning
Hongzhan Lin, Jing Ma, Liangliang Chen, Zhiwei Yang, Mingfei Cheng, Guang Chen
Low Resource Rumor Detection Adversarial Contrastive Learning Rumor Indicative Signal Rumor Detection Model

November 26, 2021

Simple Contrastive Representation Adversarial Learning for NLP Tasks
Deshui Miao, Jiaqi Zhang, Wenbo Xie, Jian Song, Xin Li, Lijuan Jia, Ning Guo
Contrastive Learning Adversarial Example Adversarial Training Contrastive Loss NLP Task Adversarial Contrastive Learning Adversarial Contrastive

Adversarial Contrastive Learning

Papers

FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive Learning

LAMP: Learnable Meta-Path Guided Adversarial Contrastive Learning for Heterogeneous Graphs

Adversarial Contrastive Learning Based Physics-Informed Temporal Networks for Cuffless Blood Pressure Estimation

Surgical-VQLA++: Adversarial Contrastive Learning for Calibrated Robust Visual Question-Localized Answering in Robotic Surgery

Contrastive-Adversarial and Diffusion: Exploring pre-training and fine-tuning strategies for sulcal identification

Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning

Graph Contrastive Learning with Generative Adversarial Network

Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations

Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization

Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning

Generalization Bounds for Adversarial Contrastive Learning

Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection

Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks

Adversarial Lagrangian Integrated Contrastive Embedding for Limited Size Datasets

PointACL:Adversarial Contrastive Learning for Robust Point Clouds Representation under Adversarial Attack

Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness

Adversarial Contrastive Learning via Asymmetric InfoNCE

Adversarial Contrastive Learning by Permuting Cluster Assignments

Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learning

Simple Contrastive Representation Adversarial Learning for NLP Tasks