Contrastive Learning Framework

Contrastive learning frameworks aim to learn robust and informative representations by comparing similar (positive) and dissimilar (negative) data points. Current research focuses on applying this technique across diverse modalities, including text, images, graphs, and multimodal data, often employing variations of contrastive loss functions within neural network architectures. These frameworks are proving valuable for improving performance in various downstream tasks, such as classification, regression, clustering, and recommendation systems, particularly in scenarios with limited labeled data or complex data structures. The resulting advancements have significant implications for various fields, including natural language processing, computer vision, and recommendation systems.

Papers

December 17, 2023

CLDR: Contrastive Learning Drug Response Models from Natural Language Supervision
Kun Li, Wenbin Hu
Contrastive Learning Framework Language Supervision Drug Response Prediction Drug Response Regression Representation

November 10, 2023

TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation
Zixiang Xian, Rubing Huang, Dave Towey, Chunrong Fang, Zhenyu Chen
Transfer Learning Real World Code Code Representation Contrastive Learning Framework Code Clone Detection Code Transformation

November 1, 2023

REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning
Maxwell A. Xu, Alexander Moreno, Hui Wei, Benjamin M. Marlin, James M. Rehg
Full State Reconstruction Contrastive Self Supervised Learning Contrastive Learning Framework Time Series Contrastive Learning Retrieval Based Reconstruction

May 24, 2023

Contrastive Learning of Sentence Embeddings from Scratch
Junlei Zhang, Zhenzhong Lan, Junxian He
Contrastive Learning Sentence Embeddings Scratch Project Contrastive Learning Framework

May 22, 2023

Sentence Representations via Gaussian Embedding
Shohei Yoda, Hayato Tsukagoshi, Ryohei Sasano, Koichi Takeda
Textual Entailment RSD Difference of Gaussian Sentence Representation Semantic Textual Similarity Contrastive Learning Framework Natural Language Inference Task

May 16, 2023

ContrastNet: A Contrastive Learning Framework for Few-Shot Text Classification
Junfan Chen, Richong Zhang, Yongyi Mao, Jie Xu
Text Classification Contrastive Learning Framework Shot Text Classification Contrastive Regularization Multi Network Contrastive Learning

April 1, 2023

Towards Understanding the Mechanism of Contrastive Learning via Similarity Structure: A Theoretical Analysis
Hiroki Waida, Yuichiro Wada, Léo Andéol, Takumi Nakagawa, Yuhui Zhang, Takafumi Kanamori
Contrastive Learning Contrastive Loss Theoretical Analysis Functional Mechanism Contrastive Learning Framework Structural Similarity

February 9, 2023

Detecting Contextomized Quotes in News Headlines by Contrastive Learning
Seonyeong Song, Hyeonho Song, Kunwoo Park, Jiyoung Han, Meeyoung Cha
Contrastive Learning Jina Embeddings News Article Contrastive Learning Framework Quotation Attribution Quotation Extraction

February 5, 2023

Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation
Junjie Huang, Qi Cao, Ruobing Xie, Shaoliang Zhang, Feng Xia, Huawei Shen, Xueqi Cheng
Graph Neural Network Contrastive Learning Contrastive Loss Effective Recommendation Contrastive Learning Framework

January 26, 2023

Graph Contrastive Learning for Skeleton-based Action Recognition
Xiaohu Huang, Hao Zhou, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Jingdong Wang, Xinggang Wang, Wenyu Liu, Bin Feng
Convolutional Neural Network Contrastive Learning Skeleton Based Action Recognition Contrastive Learning Framework Skeleton Graph

December 1, 2022

November 19, 2022

Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structure
Ke Liang, Yue Liu, Sihang Zhou, Wenxuan Tu, Yi Wen, Xihong Yang, Xiangjun Dong, Xinwang Liu
Contrastive Learning Knowledge Graph Graph Learning Contrastive Learning Framework Contrastive Pair Relational Structure Knowledge Graph Contrastive

October 29, 2022

Differentiable Data Augmentation for Contrastive Sentence Representation Learning
Tianduo Wang, Wei Lu
Contrastive Learning Contrastive Learning Framework Contrastive Fine Tuning Contrastive Sentence

October 17, 2022

Watch the Neighbors: A Unified K-Nearest Neighbor Contrastive Learning Framework for OOD Intent Discovery
Yutao Mou, Keqing He, Pei Wang, Yanan Wu, Jingang Wang, Wei Wu, Weiran Xu
Unified Alignment Thy Neighbor Contrastive Learning Framework Domain Detection Multi Domain Training Domain Intent Nearest Neighbor Contrastive Learning

September 17, 2022

Few-Shot Classification with Contrastive Learning
Zhanyuan Yang, Jinghua Wang, Yingying Zhu
Contrastive Learning Classification Code Shot Learning Contrastive Learning Framework Two Stage Training Supervised Contrastive Loss

September 14, 2022

Joint Debiased Representation and Image Clustering Learning with Self-Supervision
Shunjie-Fabian Zheng, JaeEun Nam, Emilio Dorigatti, Bernd Bischl, Shekoofeh Azizi, Mina Rezaei
Contrastive Learning Contrastive Loss Self Supervision Visual Representation Learning Joint Representation Contrastive Learning Framework Image Clustering Debiased Contrastive

September 6, 2022

September 4, 2022

Representative Image Feature Extraction via Contrastive Learning Pretraining for Chest X-ray Report Generation
Yu-Jen Chen, Wei-Hsiang Shen, Hao-Wei Chung, Ching-Hao Chiu, Da-Cheng Juan, Tsung-Ying Ho, Chi-Tung Cheng, Meng-Lin Li, Tsung-Yi Ho
Contrastive Learning Visual Representation Contrastive Learning Framework Lung Segmentation Medical Report Generation Contrastive Pretraining Chest X Ray Report Generation

Contrastive Learning Framework

Papers

CLDR: Contrastive Learning Drug Response Models from Natural Language Supervision

TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation

REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning

Contrastive Learning of Sentence Embeddings from Scratch

Sentence Representations via Gaussian Embedding

ContrastNet: A Contrastive Learning Framework for Few-Shot Text Classification

Towards Understanding the Mechanism of Contrastive Learning via Similarity Structure: A Theoretical Analysis

Detecting Contextomized Quotes in News Headlines by Contrastive Learning

Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation

Graph Contrastive Learning for Skeleton-based Action Recognition

Hyperbolic Contrastive Learning for Visual Representations beyond Objects

CL4CTR: A Contrastive Learning Framework for CTR Prediction

Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structure

Differentiable Data Augmentation for Contrastive Sentence Representation Learning

Watch the Neighbors: A Unified K-Nearest Neighbor Contrastive Learning Framework for OOD Intent Discovery

Few-Shot Classification with Contrastive Learning

Joint Debiased Representation and Image Clustering Learning with Self-Supervision

SimCLF: A Simple Contrastive Learning Framework for Function-level Binary Embeddings

Multimodal contrastive learning for remote sensing tasks

Representative Image Feature Extraction via Contrastive Learning Pretraining for Chest X-ray Report Generation