A Systematic Literature Review of Adapter-based Approaches to Knowledge-enhanced Language Models
Authors: Alexander M. Fichtl, Juraj Vladika


Reviewer paper summaries: This paper provide a fine-grained comparison between different Adapter-based Approaches to Knowledge-enhanced Language Models. It provides some quantitive comparison between approaches regarding different knowledge types. The comparisons are detailed, however, the paper can be further improved in terms of writing and giving some insights.
Summary of strengths: 1. The studied problem is new. The author provide a fine-grained survey on specific Knowledge-enhanced Language Models, which involves adapter-based methods
2. The paper provide distribution of published papers on different adaptor methods, which is interesting
Summary of weaknesses: 1. The scope of this paper is confusing. The survey focuses on adapter-based knowledge graph enhanced LLM, making the scope very narrow and less meaningful. To be more specific, there are many other works on using other parameter-efficent fine-tuning for knowledge injection into LLMs, or PEFT with knowledge bases (not knowledge graphs) for enhancing LLM. Is there any specific reason to only consider adaptor and KG based enhancing methods? The narrow scope makes the survey less meaningful. 
2. The writing and presentation of the paper needs significant improvement. The introduction has a lot of statement without citation. There are only 2 citations in the intro. Figure 2 takes up too much space. It could be made one-column. When discussing about the quantitive analysis, specific table or figure needs to be referred to.
3. Since the paper only focuses on a small topic, why didn't the work provide more experimental results to show the advantages or rankings of different methods? Simply calculating the stats of published paper is less interesting. Also, the author only provide some insights in page 8, which only summarize the performance improvement in original papers, without any new insights, like when should I choose one typical design for the adapter.
Comments, suggestions and typos: please see above
Overall assessment scores: 2