Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework | Paper Citation Record

Observation 31ba62ba-b6ac-4abe-a7f0-0ff59172501f · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Learning transferable visual models from natural language supervision,

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This paper cites One for all: Towards training one graph model for all classification tasks,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework One for all: Towards training one graph model for all classification tasks,

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This paper cites Unigraph: Learning a unified cross- domain foundation model for text-attributed graphs,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Unigraph: Learning a unified cross- domain foundation model for text-attributed graphs,

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This paper cites AnyGraph: Graph Foundation Model in the Wild.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework AnyGraph: Graph Foundation Model in the Wild

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Observation c1417b5b-743c-4f8c-8608-c7df1498f1ee · outbound

This paper cites Advances and open problems in federated learning,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Advances and open problems in federated learning,

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This paper cites Federated learning for generalization, robustness, fairness: A survey and benchmark,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Federated learning for generalization, robustness, fairness: A survey and benchmark,

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This paper cites Subgraph federated learning with missing neighbor generation,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Subgraph federated learning with missing neighbor generation,

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This paper cites Personalized subgraph federated learning,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Personalized subgraph federated learning,

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This paper cites Towards effective fed- erated graph foundation model via mitigating knowledge entanglement,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Towards effective fed- erated graph foundation model via mitigating knowledge entanglement,

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This paper cites Fedbook: A unified federated graph foundation codebook with intra- domain and inter-domain knowledge modeling,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Fedbook: A unified federated graph foundation codebook with intra- domain and inter-domain knowledge modeling,

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This paper cites Sinkhorn distances: Lightspeed computation of optimal transport,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Sinkhorn distances: Lightspeed computation of optimal transport,

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This paper cites Optimal transport for domain adaptation,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Optimal transport for domain adaptation,

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This paper cites Multimodal deep learning,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Multimodal deep learning,

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This paper cites Mmgcn: Multi-modal graph convolution network for personalized recommenda- tion of micro-video,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Mmgcn: Multi-modal graph convolution network for personalized recommenda- tion of micro-video,

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This paper cites Semi-supervised classification with graph convolutional networks,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Semi-supervised classification with graph convolutional networks,

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This paper cites Communication-efficient learning of deep networks from decentralized data,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Communication-efficient learning of deep networks from decentralized data,

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This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework The Power of Scale for Parameter-Efficient Prompt Tuning

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This paper cites Learning to prompt for vision- language models,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Learning to prompt for vision- language models,

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This paper cites A survey on self-supervised learning: Algorithms, applications, and future trends,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework A survey on self-supervised learning: Algorithms, applications, and future trends,

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This paper cites A bayesian federated learning framework with online laplace approxima- tion,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework A bayesian federated learning framework with online laplace approxima- tion,

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This paper cites Rethinking federated graph foundation models: A graph-language alignment-based approach,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Rethinking federated graph foundation models: A graph-language alignment-based approach,

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This paper cites Cross-modal federated human activity recognition,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Cross-modal federated human activity recognition,

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This paper cites Federated feature augmentation and alignment,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Federated feature augmentation and alignment,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Fedgta: Topology-aware averaging for federated graph learning,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Federated graph semantic and structural learning,

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This paper cites Fedtad: Topology- aware data-free knowledge distillation for subgraph federated learning,.

Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Fedtad: Topology- aware data-free knowledge distillation for subgraph federated learning,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Federated graph classification over non-iid graphs,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Fedproto: Federated prototype learning across heterogeneous clients,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Adafgl: A new paradigm for federated node classification with topology heterogeneity,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Federatedscope-gnn: Towards a unified, comprehensive and efficient package for federated graph learning,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Utility- preserving federated graph learning with dual-perspective fairness,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Federated learning of generalized linear causal networks,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Gft: Graph foundation model with transferable tree vocabulary,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Variational graph auto-encoders,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Deep graph infomax,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Multimodal learning with transform- ers: A survey,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework CAMPA: Efficient and Aligned Multimodal Graph Learning via Decoupled Propagation and Aggregation

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Toward effective multimodal graph foundation model: A divide-and- conquer based approach,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Graph attention networks,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework A kernel two-sample test,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Mm-openfgl: A comprehensive benchmark for multimodal federated graph learning,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Fast unfolding of communities in large networks,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Multiplex Graph Networks for Multimodal Brain Network Analysis

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Exploring the limits of transfer learning with a unified text-to-text transformer,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework GraphMAE: Self-Supervised Masked Graph Autoencoders

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Neural discrete representation learning,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Federated optimization in heterogeneous networks,

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Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework Ditto: Fair and robust federated learning through personalization,

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