Device and computer-implemented method for operating a knowledge base comprising a language model

A device for operating a knowledge base including a language model, wherein the language model is pre-trained for a first domain and includes a tokenizer and a transformer, the device comprising:

• at least one processor;
• and
• at least one non-transitory storage;
• wherein the at least one processor is configured to process instructions that, when executed by the at least one processor, cause the at least one processor to perform the following steps:
• providing an input sentence of a second domain;
• tokenizing the input sentence with the tokenizer into tokens;
• determining, by the transformer, respective embeddings for the individual tokens of the input sentence;
• transforming the tokens with the transformer to a sentence embedding representing the input sentence as a whole;
• identifying the input sentence as belonging to the second domain;
• selecting, based on the identification, a set of keywords of the second domain;
• providing a first set of embeddings that includes:
• a prompt embedding of the first domain;
• and
• the respective embeddings of the individual tokens of the input sentence;
• providing a second set of embeddings that includes:
• the first set of embeddings;
• and
• a set of embeddings that represent the selected keywords of the second domain;
• determining, based on the sentence embedding, a respective weight for the first set of embeddings and a respective weight for the second set of embeddings;
• blending the first set of embeddings and the second set of embeddings according to the respective weights to determine a blended prompt;
• and
• transforming, with the transformer, at least one of the tokens and the blended prompt to an output of the knowledge base;
• wherein the at least one storage is configured to store the instructions and the knowledge base.

A non-transitory computer-readable medium on which is stored a computer program for operating a knowledge base including a language model that is pre-trained for a first domain, the computer program including computer readable instructions that, when executed by a computer, cause the computer to perform the following steps:

• providing an input sentence of a second domain;
• tokenizing the input sentence with a tokenizer into tokens;
• determining, by a transformer, respective embeddings for the individual tokens of the input sentence;
• transforming the tokens with the transformer to a sentence embedding representing the input sentence as a whole;
• identifying the input sentence as belonging to the second domain;
• selecting, based on the identification, a set of keywords of the second domain;
• providing a first set of embeddings that includes:
• a prompt embedding of the first domain;
• and
• the respective embeddings of the individual tokens of the input sentence;
• providing a second set of embeddings that includes:
• the first set of embeddings;
• and
• a set of embeddings that represent the selected keywords of the second domain;
• determining, based on the sentence embedding, a respective weight for the first set of embeddings and a respective weight for the second set of embeddings;
• blending the first set of embeddings and the second set of embeddings according to the respective weights to determine a blended prompt;
• and
• transforming, with the transformer, at least one of the tokens and the blended prompt to an output of the knowledge base.