Generation of natural language (NL) based summaries using a large language model (LLM) and subsequent modification thereof for attribution

A system comprising:

• at least one processor;
• and
• memory storing instructions that, when executed by the at least one processor, cause the at least one processor to be operable to:
• receive, from a third-party, a third-party dataset;
• fine-tune, based on the third-party dataset, a large language model (LLM) that was initially trained on a LLM dataset;
• receive natural language (NL) based input associated with a client device of the third-party;
• generate, based on processing the NL based input using the LLM that was initially trained on the LLM dataset and that was fine-tuned on the third-party dataset, a NL based response that is responsive to the NL based input;
• process the NL based response to determine whether a NL based response segment, of the NL based response, matches a third-party dataset segment, of the third-party dataset that was utilized to fine-tune the LLM, based on comparing a plurality of NL based response segments, of the NL based response, to a plurality of third-party dataset segments, of the third-party dataset that was utilized to fine-tune the LLM;
• and
• in response to determining that a NL based response segment of the NL based response matches a third-party dataset segment of the third-party dataset that was utilized to fine-tune the LLM:
• cause, to be rendered at the client device:
• an indication of the NL based response segment of the NL based response that matches the third-party dataset segment of the third-party dataset that was utilized to fine-tune the LLM;
• and
• a hyperlink, included in the NL based response segment of the NL based response, to a document that includes the third-party dataset segment of the third-party dataset that was utilized to fine-tune the LLM, wherein the hyperlink, when selected, causes the client device to navigate to the document that includes the third-party dataset segment of the third-party dataset that was utilized to fine-tune the LLM.

A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations, the operations comprising:

• receiving, from a third-party, a third-party dataset;
• fine-tuning, based on the third-party dataset, a large language model (LLM) that was initially trained on a LLM dataset;
• receiving natural language (NL) based input associated with a client device of the third-party;
• generating, based on processing the NL based input using the LLM that was initially trained on the LLM dataset and that was fine-tuned on the third-party dataset, a NL based response that is responsive to the NL based input;
• processing the NL based response to determine whether a NL based response segment, of the NL based response, matches a third-party dataset segment, of the third-party dataset that was utilized to fine-tune the LLM, based on comparing a plurality of NL based response segments, of the NL based response, to a plurality of third-party dataset segments, of the third-party dataset that was utilized to fine-tune the LLM;
• and
• in response to determining that a NL based response segment of the NL based response matches a third-party dataset segment of the third-party dataset that was utilized to fine-tune the LLM:
• causing, to be rendered at the client device:
• an indication of the NL based response segment of the NL based response that matches the third-party dataset segment of the third-party dataset that was utilized to fine-tune the LLM;
• and
• a hyperlink, included in the NL based response segment of the NL based response, to a document that includes the third-party dataset segment of the third-party dataset that was utilized to fine-tune the LLM, wherein the hyperlink, when selected, causes the client device to navigate to the document that includes the third-party dataset segment of the third-party dataset that was utilized to fine-tune the LLM.