Ranking-aware contrastive learning with large language models
Generating high-quality word and sentence representations is a foundational task in natural language processing (NLP). In recent years, various embedding methodologies have been proposed, notably those leveraging the capabilities of large language models for in-context learning. Research has shown t...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/177983 |