Can Large Language Models Serve as Effective Classifiers for Hierarchical Multi-Label Classification of Scientific Documents at Industrial Scale?

Keyphrases

• Scientific Documents 100%
• Hierarchical multi-label Classification 100%
• Large Language Models 100%
• Dynamic Taxonomy 40%
• Zero-shot 20%
• Rapid Growth 20%
• Machine Learning Approach 20%
• Document Classification 20%
• Labeled Data 20%
• Preprints 20%
• Evaluation Framework 20%
• Traditional Machine Learning 20%
• Multiple Disciplines 20%
• Multi-label Classification 20%
• Cost Efficiency 20%
• Classification Accuracy 20%
• Class number 20%
• Classification Cost 20%
• Label Assignment 20%
• Model Adaptation 20%
• Time Label 20%
• Dynamic Labels 20%
• Input Limits 20%
• Unique Challenge 20%
• Retrieval Method 20%
• Number of Nodes 20%
• Approach-avoid 20%
• Dense Retrieval 20%

Computer Science

• Scientific Document 100%
• Multi-Label Classification 100%
• Large Language Model 100%
• Machine Learning Approach 20%
• Document Classification 20%
• Data Model 20%
• Information Retrieval 20%
• Complex Task 20%
• Classification Accuracy 20%
• Model Adaptation 20%
• Zero-Shot Learning 20%