Domain-specific text embedding model for accelerator physics
Accelerator physics presents unique challenges for natural language processing (NLP) due to its specialized terminology and complex concepts. A key component in overcoming these challenges is the development of robust text embedding models that transform textual data into dense vector representation...
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| Main Authors: | Thorsten Hellert, João Montenegro, Marco Venturini, Andrea Pollastro |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2025-04-01
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| Series: | Physical Review Accelerators and Beams |
| Online Access: | http://doi.org/10.1103/PhysRevAccelBeams.28.044601 |
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