Summary of The Role Of Transformer Models in Advancing Blockchain Technology: a Systematic Survey, by Tianxu Liu et al.
The Role of Transformer Models in Advancing Blockchain Technology: A Systematic Survey
by Tianxu Liu, Yanbin Wang, Jianguo Sun, Ye Tian, Yanyu Huang, Tao Xue, Peiyue Li, Yiwei Liu
First submitted to arxiv on: 2 Sep 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper bridges the gap in Transformer applications in blockchain by surveying over 200 relevant papers, reviewing practical cases and research progress. It covers key areas like anomaly detection, smart contract security analysis, cryptocurrency prediction, trend analysis, and code summary generation. The authors adopt a domain-oriented classification system to organize and introduce representative methods based on major challenges in current blockchain research. For each research domain, they provide background, objectives, previous methods, limitations, and advancements brought by Transformer models. Additionally, the paper discusses challenges like data privacy, model complexity, and real-time processing requirements, proposing future research directions for integrated development of blockchain technology and machine learning. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps to understand how a powerful technology called Transformers can be used in blockchains. Blockchains need to be more efficient, secure, and fast, and this paper looks at over 200 studies on using Transformers to make that happen. It covers different areas like finding unusual things, analyzing smart contracts, predicting cryptocurrency prices, and generating summaries of code. The authors organize their findings by the types of blockchain challenges they address. They also talk about some problems with using Transformers in blockchains, like keeping data private and processing information quickly. |
Keywords
* Artificial intelligence * Anomaly detection * Classification * Machine learning * Transformer
