Cover Image

Learning over Positive and Negative Edges with Contrastive Message Passing

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pao-Huang, Peter, Kanatsoulis, Charilaos I., Bereket, Michael, Leskovec, Jure
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RelGNN: Composite Message Passing for Relational Deep Learning
by: Chen, Tianlang, et al.
Published: (2025)

Learning Efficient Positional Encodings with Graph Neural Networks
by: Kanatsoulis, Charilaos I., et al.
Published: (2025)

Relational Deep Learning: Challenges, Foundations and Next-Generation Architectures
by: Dwivedi, Vijay Prakash, et al.
Published: (2025)

Uncalibrated Reasoning: GRPO Induces Overconfidence for Stochastic Outcomes
by: Bereket, Michael, et al.
Published: (2025)

WindMiL: Equivariant Graph Learning for Wind Loading Prediction
by: Vargiemezis, Themistoklis, et al.
Published: (2025)

Relational Graph Transformer
by: Dwivedi, Vijay Prakash, et al.
Published: (2025)

Position: Message-passing and spectral GNNs are two sides of the same coin
by: Vasileiou, Antonis, et al.
Published: (2026)

T-GAE: Transferable Graph Autoencoder for Network Alignment
by: He, Jiashu, et al.
Published: (2023)

Solving Large-scale Spatial Problems with Convolutional Neural Networks
by: Owerko, Damian, et al.
Published: (2023)

Relational Transformer: Toward Zero-Shot Foundation Models for Relational Data
by: Ranjan, Rishabh, et al.
Published: (2025)

RelBench v2: A Large-Scale Benchmark and Repository for Relational Data
by: Gu, Justin, et al.
Published: (2026)

MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
by: Huang, Qian, et al.
Published: (2023)

Why Does Dropping Edges Usually Outperform Adding Edges in Graph Contrastive Learning?
by: Xu, Yanchen, et al.
Published: (2024)

Multi-Target Tracking with Transferable Convolutional Neural Networks
by: Owerko, Damian, et al.
Published: (2022)

Expressive Power of Temporal Message Passing
by: Wałęga, Przemysław Andrzej, et al.
Published: (2024)

Large Language Models are Good Relational Learners
by: Wu, Fang, et al.
Published: (2025)

Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing
by: Lippmann, Peter, et al.
Published: (2024)

RFG: Test-Time Scaling for Diffusion Large Language Model Reasoning with Reward-Free Guidance
by: Chen, Tianlang, et al.
Published: (2025)

Towards Dynamic Message Passing on Graphs
by: Sun, Junshu, et al.
Published: (2024)

Learning Physical Simulation with Message Passing Transformer
by: Xu, Zeyi, et al.
Published: (2024)

GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts
by: Wu, Shirley, et al.
Published: (2023)

Heterophily-informed Message Passing
by: Wang, Haishan, et al.
Published: (2025)

Scale-aware Message Passing For Graph Node Classification
by: Jiang, Qin, et al.
Published: (2024)

Higher-Order Message Passing for Glycan Representation Learning
by: Joeres, Roman, et al.
Published: (2024)

Representation Learning for Frequent Subgraph Mining
by: Ying, Rex, et al.
Published: (2024)

Graph Coarsening with Message-Passing Guarantees
by: Joly, Antonin, et al.
Published: (2024)

AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning
by: Wu, Shirley, et al.
Published: (2024)

Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning
by: Marzi, Tommaso, et al.
Published: (2025)

Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
by: Wu, Tailin, et al.
Published: (2024)

TimeGraphs: Graph-based Temporal Reasoning
by: Maheshwari, Paridhi, et al.
Published: (2024)

A Geometry-Aware Message Passing Neural Network for Modeling Aerodynamics over Airfoils
by: Helwig, Jacob, et al.
Published: (2024)

Graph Unitary Message Passing
by: Qiu, Haiquan, et al.
Published: (2024)

Scalable Data Assimilation with Message Passing
by: Key, Oscar, et al.
Published: (2024)

Hypergraph-MLP: Learning on Hypergraphs without Message Passing
by: Tang, Bohan, et al.
Published: (2023)

Automated Heterogeneous Network learning with Non-Recursive Message Passing
by: Li, Zhaoqing, et al.
Published: (2025)

Scalable Message Passing Neural Networks: No Need for Attention in Large Graph Representation Learning
by: Borde, Haitz Sáez de Ocáriz, et al.
Published: (2024)

TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
by: Shi, Juntong, et al.
Published: (2024)

Training-Free Message Passing for Learning on Hypergraphs
by: Tang, Bohan, et al.
Published: (2024)

Invariant-Based Weight Sharing for Message Passing
by: Seiffarth, Florian
Published: (2026)

Optimality of Message-Passing Architectures for Sparse Graphs
by: Baranwal, Aseem, et al.
Published: (2023)