Large language model augmentation with definite finite automaton
AssigneeNEC Laboratories America, Inc.
InventorsYiyou Sun, Haifeng Chen
Life of this patent
Estimating the term…
Abstract
Systems and methods for tagging a user prompted conversation to generate contextually relevant user tags from a user prompt according to pre-populated tags in a Definite Finite Automaton (DFA) tree, navigating the DFA tree according to tags to determine a user prompted conversation state, accessing dialog identifications of previous conversations that are similar that are associated with the user prompted conversation state, compiling an LLM prompt for forming a response to the user prompted conversation, and generating a response to the user based on the prompt.
Claims20
A computer implemented method comprising:
- tagging a user prompted conversation to generate contextually relevant user tags from a user prompt according to pre-populated tags in a Definite Finite Automaton (DFA) tree;
- navigating the DFA tree according to tags to determine a user prompted conversation state;
- accessing dialog identifications of previous conversations that are similar that are associated with the user prompted conversation state;
- compiling an LLM prompt for forming a response to the user prompted conversation;
- and
- generating a response to the user based on the prompt.
A system, comprising:
- a hardware processor;
- and
- a memory that stores a computer program which, when executed by the hardware processor, causes the hardware processor to:
- tag a user prompted conversation to generate contextually relevant user tags from a user prompt according to pre-populated tags in a Definite Finite Automaton (DFA) tree;
- navigate the DFA tree according to tags to determine a user prompted conversation state;
- access dialog identifications of previous conversations that are similar that are associated with the user prompted conversation state;
- compile an LLM prompt for forming a response to the user prompted conversation;
- and
- generate a response to the user based on the prompt.
A computer program product comprising a non-transitory computer-readable storage medium containing computer program code, the computer program code when executed by one or more processors causes the one or more processors to perform operations, the computer program code comprising instructions to:
- tag a user prompted conversation to generate contextually relevant user tags from a user prompt according to pre-populated tags in a Definite Finite Automaton (DFA) tree;
- navigate the DFA tree according to tags to determine a user prompted conversation state;
- access dialog identifications of previous conversations that are similar that are associated with the user prompted conversation state;
- compile an LLM prompt for forming a response to the user prompted conversation;
- and
- generate a response to the user based on the prompt.
Dependencies are inferred from the claim text.