公开(公告)号：US20230376697A1

公开(公告)日：2023-11-23

申请号：US18173495

申请日：2023-02-23

Applicant: Google LLC

Inventor： Yinlam Chow ,  Ofir Nachum ,  Azamat Tulepbergenov

IPC: G06F40/35 ,  G06N3/092 ,  G06F40/126

CPC classification number: G06F40/35 ,  G06N3/092 ,  G06F40/126

Abstract: Systems and methods for dialogue response prediction can leverage a plurality of machine-learned language models to generate a plurality of candidate outputs, which can be processed by a dialogue management model to determine a predicted dialogue response. The plurality of machine-learned language models can include a plurality of experts trained on different intents, emotions, and/or tasks. The particular candidate output selected may be selected by the dialogue management model based on semantics determined based on a language representation. The language representation can be a representation generated by processing the conversation history of a conversation to determine conversation semantics.

公开(公告)号：US20250111157A1

公开(公告)日：2025-04-03

申请号：US18900500

申请日：2024-09-27

Applicant: Google LLC

Inventor： Guy Tennenholtz ,  Yinlam Chow ,  Chih-wei Hsu ,  Jihwan Jeong ,  Lior Shani ,  Deepak Ramachandran ,  Martin Mirolyubov Mladenov ,  Craig Edgar Boutilier

IPC: G06F40/284 ,  G06F40/40 ,  G06N3/0455

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for analyzing embedding spaces using large language models. In one aspect, a method performed by one or more computers for analyzing a target embedding space using a neural network configured to perform a set of machine learning tasks is described. The method includes: obtaining, for each of one or more entities, a respective domain embedding representing the entity in the target embedding space; receiving a text prompt including a sequence of input tokens describing a particular machine learning task in the set to be performed on the one or more entities; preparing, for the neural network, an input sequence including each input token in the text prompt and each domain embedding; and processing the input sequence, using the neural network, to generate a sequence of output tokens describing a result of the particular machine learning task.