Cover Image

Jensen-Shannon Divergence Message-Passing for Rich-Text Graph Representation Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Zuo, Yuan, Ye
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Representation Jensen-Shannon Divergence
by: Hoyos-Osorio, Jhoan K., et al.
Published: (2023)

Connecting Jensen-Shannon and Kullback-Leibler Divergences: A New Bound for Representation Learning
by: Dorent, Reuben, et al.
Published: (2025)

Black-Box Detection of LLM-Generated Text Using Generalized Jensen-Shannon Divergence
by: Chen, Shuangyi, et al.
Published: (2025)

LLM as Graph Kernel: Rethinking Message Passing on Text-Rich Graphs
by: Zhang, Ying, et al.
Published: (2026)

JEDI: The Force of Jensen-Shannon Divergence in Disentangling Diffusion Models
by: Bill, Eric Tillmann, et al.
Published: (2025)

Jensen-Shannon Divergence Based Novel Loss Functions for Bayesian Neural Networks
by: Thiagarajan, Ponkrshnan, et al.
Published: (2022)

Geometric Jensen-Shannon Divergence Between Gaussian Measures On Hilbert Space
by: Quang, Minh Ha, et al.
Published: (2025)

Multiclass Local Calibration with the Jensen-Shannon Distance
by: Barbera, Cesare, et al.
Published: (2025)

Enhancing Graph Representations with Neighborhood-Contextualized Message-Passing
by: Lim, Brian Godwin, et al.
Published: (2025)

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

Deep Clustering using Dirichlet Process Gaussian Mixture and Alpha Jensen-Shannon Divergence Clustering Loss
by: Lim, Kart-Leong
Published: (2024)

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

Two tales for a geometric Jensen--Shannon divergence
by: Nielsen, Frank
Published: (2025)

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

DyJR: Preserving Diversity in Reinforcement Learning with Verifiable Rewards via Dynamic Jensen-Shannon Replay
by: Li, Long, et al.
Published: (2026)

Attributing Response to Context: A Jensen-Shannon Divergence Driven Mechanistic Study of Context Attribution in Retrieval-Augmented Generation
by: Li, Ruizhe, et al.
Published: (2025)

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

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

Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
by: Liang, Langzhang, et al.
Published: (2024)

Beyond Message Passing: A Symbolic Alternative for Expressive and Interpretable Graph Learning
by: Geng, Chuqin, et al.
Published: (2026)

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

Convexified Message-Passing Graph Neural Networks
by: Cohen, Saar, et al.
Published: (2025)

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

'Si'multaneous 'S'patial-'T'emporal Message Passing for Dynamic Graph Representation Learning
by: Roy, Shubhajit, et al.
Published: (2026)

Beyond Message Passing: Neural Graph Pattern Machine
by: Wang, Zehong, et al.
Published: (2025)

A Novel Solution for Zero-Day Attack Detection in IDS using Self-Attention and Jensen-Shannon Divergence in WGAN-GP
by: Mu, Ziyu, et al.
Published: (2026)

Neural Message-Passing on Attention Graphs for Hallucination Detection
by: Frasca, Fabrizio, et al.
Published: (2025)

Concept Graph Convolutions: Message Passing in the Concept Space
by: Magister, Lucie Charlotte, et al.
Published: (2026)

From Message-Passing to Linearized Graph Sequence Models
by: Mathys, Joël, et al.
Published: (2026)

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

Multi-Scale Harmonic Encoding for Feature-Wise Graph Message Passing
by: Li, Longlong, et al.
Published: (2025)

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

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks
by: Bose, Kushal, et al.
Published: (2025)

Next Level Message-Passing with Hierarchical Support Graphs
by: Vonessen, Carlos, et al.
Published: (2024)

Probability Passing for Graph Neural Networks: Graph Structure and Representations Joint Learning
by: Wang, Ziyan, et al.
Published: (2024)

Tensor Graph Convolutional Network for Dynamic Graph Representation Learning
by: Wang, Ling, et al.
Published: (2024)

Parameter-Free Structural-Diversity Message Passing for Graph Neural Networks
by: Kong, Mingyue, et al.
Published: (2025)

FIMP: Foundation Model-Informed Message Passing for Graph Neural Networks
by: Rizvi, Syed Asad, et al.
Published: (2022)

Revisiting the Message Passing in Heterophilous Graph Neural Networks
by: Zheng, Zhuonan, et al.
Published: (2024)

Symbolic Graph Intelligence: Hypervector Message Passing for Learning Graph-Level Patterns with Tsetlin Machines
by: Blakely, Christian D.
Published: (2025)