Jun 24, 2024 · By providing a diverse set of datasets and benchmarks, MM-GRAPH enables researchers to evaluate and compare their models in realistic settings, ...

Jun 24, 2024 · These benchmarks aim to evaluate the performance of graph neural networks (GNNs) and other graph learning algorithms on different graph ...

The Multimodal Graph Benchmark (MM-GRAPH) is introduced, the first comprehensive multi-modal graph benchmark that incorporates both textual and visual ...

This is the official repository of paper Multimodal Graph Benchmark. Installation. # Clone the repo git clone https://github.com/mm-graph ...

We also propose a Multi-Modal Chart Benchmark (MMC-Benchmark), a comprehensive human-annotated benchmark with nine distinct tasks evaluating reasoning ...

Multi-modal knowledge graphs (MMKGs) combine different modal data (eg, text and image) for a comprehensive understanding of entities.

MM-GRAPH aims to foster research on multimodal graph learning and drive the development of more advanced and robust graph learning algorithms. By providing a ...

To bridge this gap, we introduce the Multimodal Graph Benchmark (MM-GRAPH), the first comprehensive multi-modal graph benchmark that incorporates both textual ...

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