Concatenating k-nearest-neighbor context from domain and in-domain text during continual pretraining improves German process-industry semantic search at roughly one quarter of the GPU cost of standard DAPT.
https://data.dnb.de/ FreieOnlineHochschulschriften/ (2024), data retrieved from the source on 2024-05-06
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Efficient Domain-adaptive Continual Pretraining for the Process Industry in the German Language
Concatenating k-nearest-neighbor context from domain and in-domain text during continual pretraining improves German process-industry semantic search at roughly one quarter of the GPU cost of standard DAPT.