Knowledge Graphs for Multi-modal Learning: Survey and Perspective
Authors: Zhuo Chen, Yichi Zhang, Yin Fang, Yuxia Geng, Lingbing Guo, Wen Zhang, Jiaoyan Chen, Xiaoze Liu, Jeff Z. Pan, Lei Liang, Ningyu Zhang, Huajun Chen


Reviewer paper summaries: This paper offers a survey on knowledge graphs for multi-modal learning. After providing preliminaries including knowledge graphs and KGs acquisition for multi-modal learning, the authors give a comprehensive survey on KG-driven multi-modal learning from the perspectives of multi-modal understanding & reasoning, multi-modal classification, multi-modal generation, and KG-aware mutli-modal pre-training. Moreover, the authors also summarize challenges in this field and offer potential future research directions.
Summary of strengths: 1. KG-driven multi-modal learning is both a well-established and rapidly evolving research area. This survey may be interesting for researchers in this field, which provides a thorough and up-to-date overview.

2. The survey is notably comprehensive, citing approximately 300 papers, which is highly commendable. I appreciate the significant effort the authors have invested in compiling this paper.

3. In addition to reviewing existing works, the authors provide preliminary knowledge and summarize current challenges and potential research opportunities, making this paper particularly valuable for beginners in the field.
Summary of weaknesses: 1. The paper lacks a clear focus. While the authors initially discuss Conditioned Reflexes and Torso-to-tail Knowledge, these concepts are not mentioned in the subsequent sections. What is their relationship to KG-driven multi-modal learning? Additionally, the purpose of Figure 1 is unclear. The abstract is brief, and the entire introduction lacks citations. What is the research gap here? Why is a survey like this needed by the current NLP community?

2. The authors fail to compare existing surveys on KG-driven multi-modal learning. Is this survey the first of its kind? If so, the authors need to emphasize its significance. However, a simple web search reveals several related surveys. The authors should find and compare these surveys to highlight the unique contributions of their work, providing readers with more insights into its distinctiveness.

3. While the paper is lengthy and comprehensive, careful proofreading is needed to improve its quality. For instance, the caption of Figure 2 does not align well with the figure.
Comments, suggestions and typos: 1. When citing a paper with more than three authors, please use "et al." in the article to maintain readability. For instance, see lines 2602-2614.

2. Carefully proofread the entire document to ensure consistency. For example, review line 2518.

3. Discuss some limitations of this work. Phrases such as those on lines 644-645 are not informative and should be elaborated upon.

4. Include related surveys and provide a comparison to highlight the differences.

5. Reorganize the abstract and introduction to better highlight the contributions of this survey.
Overall assessment scores: 2