CL4nlp-dm

Contrastive learning (& some transfer learning) for natural language processing & data mining

WWW 2022

• Zero-Shot Stance Detection via Contrastive Learning Paper

AAAI 2022

ICLR 2022

• Incremental False Negative Detection for Contrastive Learning Paper
• Chaos is a Ladder: A New Understanding of Contrastive Learning Paper
• Anomaly Detection for Tabular Data with Internal Contrastive Learning Paper
• No One Representation to Rule Them All: Overlapping Features of Training Methods Paper
• Generative Models as a Data Source for Multiview Representation Learning Paper
• Revisiting Over-smoothing in BERT from the Perspective of Graph Paper
• GNN-LM: Language Modeling based on Global Contexts via GNN Paper
• A New Perspective on "How Graph Neural Networks Go Beyond Weisfeiler-Lehman?" Paper
• Expressiveness and Approximation Properties of Graph Neural Networks Paper
• Neural Structured Prediction for Inductive Node Classification Paper
• Scarf: Self-Supervised Contrastive Learning using Random Feature Corruption Paper
• Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation Paper
• MAML is a Noisy Contrastive Learner Paper
• Contrastive Learning is Just Meta-Learning Paper
• Understanding Dimensional Collapse in Contrastive Self-supervised Learning Paper
• Learning Weakly-supervised Contrastive Representations Paper
• ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning Paper
• How Does SimSiam Avoid Collapse Without Negative Samples? Towards a Unified Understanding of Progress in SSL Paper
• ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning Paper
• Open-World Semi-Supervised Learning Paper
• Poisoning and Backdooring Contrastive Learning Paper

EMNLP 2021

• SimCSE: Simple Contrastive Learning of Sentence Embeddings Paper Code

NIPS 2021

ICML 2021

• Learning Transferable Visual Models From Natural Language Supervision Paper Code

ACL 2021

NIPS 2020

• Supervised Contrastive Learning Paper

ICML 2020

• Understanding contrastive representation learning through alignment and uniformity on the hypersphere PaperCode

Arxiv & CV

• Meta-learning for Few-shot Natural Language Processing: A Survey Paper
• Momentum Contrast for Unsupervised Visual Representation Learning Paper
• Improved Baselines with Momentum Contrastive Learning Paper
• Understanding the Behaviour of Contrastive Loss Paper