Cover Image

Heterogeneous Contrastive Learning for Foundation Models and Beyond

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zheng, Lecheng, Jing, Baoyu, Li, Zihao, Tong, Hanghang, He, Jingrui
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ARIEL: Adversarial Graph Contrastive Learning
by: Feng, Shengyu, et al.
Published: (2022)

PyG-SSL: A Graph Self-Supervised Learning Toolkit
by: Zheng, Lecheng, et al.
Published: (2024)

OWLEYE: Zero-Shot Learner for Cross-Domain Graph Data Anomaly Detection
by: Zheng, Lecheng, et al.
Published: (2026)

Can Graph Neural Networks Learn Language with Extremely Weak Text Supervision?
by: Li, Zihao, et al.
Published: (2024)

Automated Contrastive Learning Strategy Search for Time Series
by: Jing, Baoyu, et al.
Published: (2024)

Multi-modal Causal Structure Learning and Root Cause Analysis
by: Zheng, Lecheng, et al.
Published: (2024)

Neural Active Learning Beyond Bandits
by: Ban, Yikun, et al.
Published: (2024)

Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative
by: Li, Zihao, et al.
Published: (2025)

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning
by: Bao, Wenxuan, et al.
Published: (2025)

Tensor Convolutional Network for Higher-Order Interaction Prediction in Sparse Tensors
by: Jang, Jun-Gi, et al.
Published: (2025)

Heterogeneous Scientific Foundation Model Collaboration
by: Li, Zihao, et al.
Published: (2026)

Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
by: Bao, Wenxuan, et al.
Published: (2024)

STERLING: Synergistic Representation Learning on Bipartite Graphs
by: Jing, Baoyu, et al.
Published: (2023)

What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs
by: Fu, Dongqi, et al.
Published: (2024)

CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
by: Liu, Zhining, et al.
Published: (2025)

ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method
by: Fu, Dongqi, et al.
Published: (2025)

Saffron-1: Safety Inference Scaling
by: Qiu, Ruizhong, et al.
Published: (2025)

Cluster Aware Graph Anomaly Detection
by: Zheng, Lecheng, et al.
Published: (2024)

Generating Fine-Grained Causality in Climate Time Series Data for Forecasting and Anomaly Detection
by: Fu, Dongqi, et al.
Published: (2024)

Fair Anomaly Detection For Imbalanced Groups
by: Wu, Ziwei, et al.
Published: (2024)

PageRank Bandits for Link Prediction
by: Ban, Yikun, et al.
Published: (2024)

PLANETALIGN: A Comprehensive Python Library for Benchmarking Network Alignment
by: Yu, Qi, et al.
Published: (2025)

SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval
by: Li, Zihao, et al.
Published: (2024)

Taming Knowledge Conflicts in Language Models
by: Li, Gaotang, et al.
Published: (2025)

Graph Data Selection for Domain Adaptation: A Model-Free Approach
by: Li, Ting-Wei, et al.
Published: (2025)

Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization
by: Qiu, Ruizhong, et al.
Published: (2024)

Adversarial Bias: Data Poisoning Attacks on Fairness
by: Chan, Eunice, et al.
Published: (2025)

Trustworthy Transfer Learning: A Survey
by: Wu, Jun, et al.
Published: (2024)

PowerGrow: Feasible Co-Growth of Structures and Dynamics for Power Grid Synthesis
by: He, Xinyu, et al.
Published: (2025)

Heterogeneous Graph Contrastive Learning with Spectral Augmentation
by: Zhang, Jing, et al.
Published: (2024)

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
by: Liu, Zhining, et al.
Published: (2025)

Class-Imbalanced Graph Learning without Class Rebalancing
by: Liu, Zhining, et al.
Published: (2023)

Federated Foundation Models on Heterogeneous Time Series
by: Chen, Shengchao, et al.
Published: (2024)

Flow Matching Meets Biology and Life Science: A Survey
by: Li, Zihao, et al.
Published: (2025)

Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach
by: Chen, Shengchao, et al.
Published: (2026)

Efficient Automatic Tuning for Data-driven Model Predictive Control via Meta-Learning
by: Li, Baoyu, et al.
Published: (2024)

APEX$^2$: Adaptive and Extreme Summarization for Personalized Knowledge Graphs
by: Li, Zihao, et al.
Published: (2024)

Learnable Spatial-Temporal Positional Encoding for Link Prediction
by: Tieu, Katherine, et al.
Published: (2025)

Provably Extending PageRank-based Local Clustering Algorithm to Weighted Directed Graphs with Self-Loops and to Hypergraphs
by: Li, Zihao, et al.
Published: (2024)

BOBA: Byzantine-Robust Federated Learning with Label Skewness
by: Bao, Wenxuan, et al.
Published: (2022)