2025
SemEval
SemEval 2025
Jim at SemEval-2025 Task 5: Multilingual BERT Ensemble
Abstract
AbstractThe SemEval-2025 Task 5 calls for the utilization of LLM capabilities to apply controlled subject labels to record descriptions in the multilingual library collection of the German National Library of Science and Technology. The multilingual BERT ensemble system described herein produces subject labels for various record types, including articles, books, conference papers, reports, and theses. Results indicate that for English language article records, bidirectional encoder-only LLMs can achieve high recall in automated subject assignment.
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Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing
Authors
Topics
Artificial Intelligence > Core AI > Multimodal Learning
Machine Learning > Core Methods > Classification
Natural Language Processing > Applications > Text Classification
Natural Language Processing > Resources & Methods > Multilingual NLP
Deep Learning > Learning Types > Ensemble Learning
Artificial Intelligence > Core AI > Multi-Lingual Learning