An Augmentation Overlap Theory of Contrastive Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Qi, Wang, Yifei, Wang, Yisen |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Non-negative Contrastive Learning
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
Do Generated Data Always Help Contrastive Learning?
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
Dissecting the Failure of Invariant Learning on Graphs
by: Wang, Qixun, et al.
Published: (2024)
by: Wang, Qixun, et al.
Published: (2024)
Can In-context Learning Really Generalize to Out-of-distribution Tasks?
by: Wang, Qixun, et al.
Published: (2024)
by: Wang, Qixun, et al.
Published: (2024)
Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective
by: Zhang, Yi-Ge, et al.
Published: (2025)
by: Zhang, Yi-Ge, et al.
Published: (2025)
LANPO: Bootstrapping Language and Numerical Feedback for Reinforcement Learning in LLMs
by: Li, Ang, et al.
Published: (2025)
by: Li, Ang, et al.
Published: (2025)
G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning
by: Guo, Xiaojun, et al.
Published: (2025)
by: Guo, Xiaojun, et al.
Published: (2025)
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
by: Zhang, Qi, et al.
Published: (2024)
by: Zhang, Qi, et al.
Published: (2024)
How to Craft Backdoors with Unlabeled Data Alone?
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
An Augmentation-Aware Theory for Self-Supervised Contrastive Learning
by: Cui, Jingyi, et al.
Published: (2025)
by: Cui, Jingyi, et al.
Published: (2025)
CAMBranch: Contrastive Learning with Augmented MILPs for Branching
by: Lin, Jiacheng, et al.
Published: (2024)
by: Lin, Jiacheng, et al.
Published: (2024)
Subgraph Networks Based Contrastive Learning
by: Wang, Jinhuan, et al.
Published: (2023)
by: Wang, Jinhuan, et al.
Published: (2023)
HiTeC: Hierarchical Contrastive Learning on Text-Attributed Hypergraph with Semantic-Aware Augmentation
by: Pan, Mengting, et al.
Published: (2025)
by: Pan, Mengting, et al.
Published: (2025)
Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning
by: Jian, Xiangru, et al.
Published: (2024)
by: Jian, Xiangru, et al.
Published: (2024)
Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification
by: Liu, Ziyu, et al.
Published: (2024)
by: Liu, Ziyu, et al.
Published: (2024)
When More is Less: Understanding Chain-of-Thought Length in LLMs
by: Wu, Yuyang, et al.
Published: (2025)
by: Wu, Yuyang, et al.
Published: (2025)
Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation
by: Zhao, Xinjian, et al.
Published: (2024)
by: Zhao, Xinjian, et al.
Published: (2024)
A Unified Theory of Sparse Dictionary Learning in Mechanistic Interpretability: Piecewise Biconvexity and Spurious Minima
by: Tang, Yiming, et al.
Published: (2025)
by: Tang, Yiming, et al.
Published: (2025)
A Closer Look at Adversarial Suffix Learning for Jailbreaking LLMs: Augmented Adversarial Trigger Learning
by: Wang, Zhe, et al.
Published: (2025)
by: Wang, Zhe, et al.
Published: (2025)
Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations
by: Wei, Zeming, et al.
Published: (2023)
by: Wei, Zeming, et al.
Published: (2023)
CGCL: Collaborative Graph Contrastive Learning without Handcrafted Graph Data Augmentations
by: Zhang, Tianyu, et al.
Published: (2021)
by: Zhang, Tianyu, et al.
Published: (2021)
Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning
by: Zhang, Yifei, et al.
Published: (2023)
by: Zhang, Yifei, et al.
Published: (2023)
Enhancing Noise Robustness of Parkinson's Disease Telemonitoring via Contrastive Feature Augmentation
by: Tang, Ziming, et al.
Published: (2025)
by: Tang, Ziming, et al.
Published: (2025)
Understanding the Role of Equivariance in Self-supervised Learning
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
Class Incremental Fault Diagnosis under Limited Fault Data via Supervised Contrastive Knowledge Distillation
by: Zhang, Hanrong, et al.
Published: (2025)
by: Zhang, Hanrong, et al.
Published: (2025)
Graph Data Augmentation with Contrastive Learning on Covariate Distribution Shift
by: Zeng, Fanlong, et al.
Published: (2025)
by: Zeng, Fanlong, et al.
Published: (2025)
Dynamic Stratified Contrastive Learning with Upstream Augmentation for MILP Branching
by: Lu, Tongkai, et al.
Published: (2025)
by: Lu, Tongkai, et al.
Published: (2025)
LAC: Graph Contrastive Learning with Learnable Augmentation in Continuous Space
by: Lin, Zhenyu, et al.
Published: (2024)
by: Lin, Zhenyu, et al.
Published: (2024)
Parallel BiLSTM-Transformer networks for forecasting chaotic dynamics
by: Ma, Junwen, et al.
Published: (2025)
by: Ma, Junwen, et al.
Published: (2025)
Machine Unlearning in Contrastive Learning
by: Wang, Zixin, et al.
Published: (2024)
by: Wang, Zixin, et al.
Published: (2024)
Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Control
by: Luo, Jinzhu, et al.
Published: (2024)
by: Luo, Jinzhu, et al.
Published: (2024)
Tabular Data Contrastive Learning via Class-Conditioned and Feature-Correlation Based Augmentation
by: Cui, Wei, et al.
Published: (2024)
by: Cui, Wei, et al.
Published: (2024)
Contrastive Multi-Task Learning with Solvent-Aware Augmentation for Drug Discovery
by: Lan, Jing, et al.
Published: (2025)
by: Lan, Jing, et al.
Published: (2025)
Open-World Test-Time Training: Self-Training with Contrast Learning
by: Su, Houcheng, et al.
Published: (2024)
by: Su, Houcheng, et al.
Published: (2024)
Rethinking Graph Contrastive Learning through Relative Similarity Preservation
by: Ning, Zhiyuan, et al.
Published: (2025)
by: Ning, Zhiyuan, et al.
Published: (2025)
CoDCL: Counterfactual-Inspired Augmentation Contrastive Learning for Temporal Link Prediction in Social Networks
by: Feng, Hantong, et al.
Published: (2026)
by: Feng, Hantong, et al.
Published: (2026)
Foundations and Frontiers of Graph Learning Theory
by: Huang, Yu, et al.
Published: (2024)
by: Huang, Yu, et al.
Published: (2024)
Deep Contrastive Graph Learning with Clustering-Oriented Guidance
by: Chen, Mulin, et al.
Published: (2024)
by: Chen, Mulin, et al.
Published: (2024)
MCLPD:Multi-view Contrastive Learning for EEG-based PD Detection Across Datasets
by: Zhang, Qian, et al.
Published: (2025)
by: Zhang, Qian, et al.
Published: (2025)
Graph Contrastive Learning with Cohesive Subgraph Awareness
by: Wu, Yucheng, et al.
Published: (2024)
by: Wu, Yucheng, et al.
Published: (2024)
Similar Items
-
Non-negative Contrastive Learning
by: Wang, Yifei, et al.
Published: (2024) -
Do Generated Data Always Help Contrastive Learning?
by: Wang, Yifei, et al.
Published: (2024) -
Dissecting the Failure of Invariant Learning on Graphs
by: Wang, Qixun, et al.
Published: (2024) -
Can In-context Learning Really Generalize to Out-of-distribution Tasks?
by: Wang, Qixun, et al.
Published: (2024) -
Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective
by: Zhang, Yi-Ge, et al.
Published: (2025)