Device, a data structure, and a computer implemented method for editing a model

A device for editing a model, comprising:

• at least one processor;
• and
• at least one non-transitory memory, wherein the at least one non-transitory memory s configured to store the model and instructions that, when executed by the at least one processor, cause the device to execute a method for editing a model, the method including the following steps:
• providing the model with parameters,
• providing a first factual sentence representing a fact to be edited, wherein the fact to be edited includes a subject, a relation, and an object, wherein the first factual sentence represents the subject and the relation,
• providing a second factual sentence representing a fact to be maintained,
• determining a prompt for requesting the model to output the object, wherein the prompt includes a concatenation of the first factual sentence and the second factual sentence, and
• editing at least one parameter of the model depending on a conditional likelihood conditioned on the subject and the relation that the model outputs a concatenation of the object and the second factual sentence in response to the prompt.

A non-transitory computer-readable medium on which is stored a computer program for editing a model, the computer program comprising computer-readable instructions that, when executed by a computer, cause the computer to execute a method for editing a model, the method comprising the following steps:

• providing the model with parameters;
• providing a first factual sentence representing a fact to be edited, wherein the fact to be edited includes a subject, a relation, and an object, wherein the first factual sentence represents the subject and the relation;
• providing a second factual sentence representing a fact to be maintained;
• determining a prompt for requesting the model to output the object, wherein the prompt includes a concatenation of the first factual sentence and the second factual sentence;
• and
• editing at least one parameter of the model depending on a conditional likelihood conditioned on the subject and the relation that the model outputs a concatenation of the object and the second factual sentence in response to the prompt.