mlsanityData to 7 Oct 2026

Learning on Multimodal Graphs: A Survey

arXiv 2402.05322 ↗First posted 7 Feb 2024cs.LG cs.AI cs.GRcited by 22

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Abstract (arXiv)

Multimodal data pervades various domains, including healthcare, social media, and transportation, where multimodal graphs play a pivotal role. Machine learning on multimodal graphs, referred to as multimodal graph learning (MGL), is essential for successful artificial intelligence (AI) applications. The burgeoning research in this field encompasses diverse graph data types and modalities, learning techniques, and application scenarios. This survey paper conducts a comparative analysis of existing works in multimodal graph learning, elucidating how multimodal learning is achieved across different graph types and exploring the characteristics of prevalent learning techniques. Additionally, we delineate significant applications of multimodal graph learning and offer insights into future directions in this domain. Consequently, this paper serves as a foundational resource for researchers seeking to comprehend existing MGL techniques and their applicability across diverse scenarios.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 29 of its 62 references that are in the map. First posted on arXiv 7 Feb 2024.

Builds on

29 of 62 references.

References · 29

  1. 2017Graph Attention Networkscited by 8,854
  2. 2017Modeling Relational Data with Graph Convolutional Networkscited by 1,684
  3. 2023MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Modelscited by 1,624
  4. 2019Simplifying Graph Convolutional Networkscited by 1,470
  5. 2020Graph Contrastive Learning with Augmentationscited by 1,203
  6. 2019Heterogeneous Graph Attention Networkcited by 732
  7. 2019KGAT: Knowledge Graph Attention Network for Recommendationcited by 342
  8. 2023A Survey on Multimodal Large Language Models for Autonomous Drivingcited by 288
  9. 2022Retrieval-Augmented Multimodal Language Modelingcited by 125
  10. 2018Learning Multimodal Graph-to-Graph Translation for Molecular Optimizationcited by 87
  11. 2022GCNet: Graph Completion Network for Incomplete Multimodal Learning in Conversationcited by 86
  12. 2023Provable Dynamic Fusion for Low-Quality Multimodal Datacited by 81
17 more
  1. 2022BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networkscited by 73
  2. 2022Simple and Efficient Heterogeneous Graph Neural Networkcited by 71
  3. 2016Image-embodied Knowledge Representation Learningcited by 68
  4. 2022Multimodal learning with graphscited by 54
  5. 2021Differentiable Scaffolding Tree for Molecular Optimizationcited by 53
  6. 2022Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completioncited by 44
  7. 2022Multimodal Analogical Reasoning over Knowledge Graphscited by 21
  8. 2023FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extractioncited by 20
  9. 2022Graph Neural Networks for Multimodal Single-Cell Data Integrationcited by 18
  10. 2023Tagging before Alignment: Integrating Multi-Modal Tags for Video-Text Retrievalcited by 18
  11. 2022Heterogeneous Graph Learning for Multi-modal Medical Data Analysiscited by 16
  12. 2022Multimodal Learning on Graphs for Disease Relation Extractioncited by 15
  13. 2022MoSE: Modality Split and Ensemble for Multimodal Knowledge Graph Completioncited by 14
  14. 2023Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matchingcited by 14
  15. 2023Joyful: Joint Modality Fusion and Graph Contrastive Learning for Multimodal Emotion Recognitioncited by 14
  16. 2022Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networkscited by 12
  17. 2023Multimodal Graph Transformer for Multimodal Question Answeringcited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 12; 2026: 9.

22 papers.

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  1. 2025Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunitiescited by 23
  2. 2025Cross-Contrastive Clustering for Multimodal Attributed Graphs with Dual Graph Filteringcited by 14
  3. 2025MLaGA: Multimodal Large Language and Graph Assistantcited by 12
  4. 2026OpenMAG: A Comprehensive Benchmark for Multimodal-Attributed Graphcited by 11
  5. 2024Multi-modal Generative AI: Multi-modal LLMs, Diffusions, and the Unificationcited by 8
  6. 2026Toward Effective Multimodal Graph Foundation Model: A Divide-and-Conquer Based Approachcited by 6
  7. 2025Transformer-Based Multimodal Knowledge Graph Completion with Link-Aware Contextscited by 1
  8. 2025Grounding the Ungrounded: A Spectral-Graph Framework for Quantifying Hallucinations in Multimodal LLMscited by 1
  9. 2025Graph Integrated Multimodal Concept Bottleneck Modelcited by 1
  10. 2025Expressive and Scalable Quantum Fusion for Multimodal Learningcited by 1
  11. 2026Towards Robust Federated Multimodal Graph Learning under Modality Heterogeneitycited by 1
  12. 2026Context-aware Modality-Topology Co-Alignment for Multimodal Attributed Graphscited by 1
10 more
  1. 2025Towards Multimodal Graph Large Language Modelcited by 0
  2. 2025Multimodal Sheaf-based Network for Glioblastoma Molecular Subtype Predictioncited by 0
  3. 2025Structure Matters: Brain Graph Augmentation via Learnable Edge Masking for Data-efficient Psychiatric Diagnosiscited by 0
  4. 2025Data-Efficient Psychiatric Disorder Detection via Self-supervised Learning on Frequency-enhanced Brain Networkscited by 0
  5. 2025SLIP: Structural-aware Language-Image Pretraining for Vision-Language Alignmentcited by 0
  6. 2026Stable Multimodal Graph Unlearning via Feature-Dimension Aware Quantile Selectioncited by 0
  7. 2026Beyond the Aggregation Dilemma: Prior-Retaining Decoupled Learning for Multimodal Graphscited by 0
  8. 2026TAHB: A Comprehensive Benchmark for Text-Attributed Hypergraph Learningcited by 0
  9. 2026ICE: Task-Aligned Clifford Latent Fields for Multimodal Graph Foundation Modelscited by 0
  10. 2026GraphSelect for Budgeted Representation Selection in Multimodal Graph Inferencecited by 0