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Engineering Challenges and Topic Clustering of 17,000 Papers
The chapter explores the engineering challenges of clustering and labeling a large number of papers using embedding models and machine learning techniques. It also discusses the use of GPT4 for labeling clusters and analyzes the differences in topic count between industry and academic authors.