-
公开(公告)号：US20250061311A1
公开(公告)日：2025-02-20
申请号：US18746532
申请日：2024-06-18
Inventor： Zeyang LEI , Siqi BAO , Hua WU , Haifeng WANG
IPC: G06N3/0475 , G06N3/08
Abstract: A data generation method is provided. The data generation method includes: generating first answer data based on first question data from a user; determining, in response to receiving negative feedback from the user for the first answer data, a first reflection result for the first answer data based on the first answer data and the negative feedback, wherein the first reflection result indicates a diagnosis reason why feedback from the user for the first answer data is negative; and generating second answer data for the first question data based on the first question data and the first reflection result.
-
公开(公告)号：US20250021610A1
公开(公告)日：2025-01-16
申请号：US18901831
申请日：2024-09-30
Inventor： Zeyang LEI , Siqi BAO , Hua WU , Haifeng WANG
IPC: G06F16/9535
Abstract: A human-machine interaction solution which relates to the field of artificial intelligence technologies, such as natural language processing technologies, large language models, deep learning technologies, or the like, is proposed. The solution may include: acquiring a question input by a user during a conversation with a large language model; retrieving memory information in a memory bank, the memory information being historical memory information about the user; and in response to retrieved memory information required for generating answer information corresponding to the question, taking the retrieved memory information as matched memory information, and generating the answer information by the large language model in conjunction with the matched memory information.
-
3.发明申请公开(公告)号：US20230075339A1
公开(公告)日：2023-03-09
申请号：US18056137
申请日：2022-11-16
Inventor： Zeyang LEI , Xinchao XU , Wenquan WU , Zhengyu Niu
IPC: G06F40/40 , G06F40/284
Abstract: The present disclosure provides a method of training an information generation model, a method of generating an information, an electronic device, and a storage medium. A specific implementation solution of the method of training the information generation model includes: splitting a description information for a target object in an information pair into at least one description word, so as to obtain a description word sequence, wherein the information pair further includes a first recommendation information; inputting the description word sequence into a dialog generation model to obtain a probability vector sequence for the target object, wherein each probability vector in the probability vector sequence includes probability values for a plurality of predetermined words; and training the dialog generation model according to the probability vector sequence and the first recommendation information, so as to obtain the information generation model.
-
4.发明申请公开(公告)号：US20250094789A1
公开(公告)日：2025-03-20
申请号：US18968810
申请日：2024-12-04
Inventor： Hua LU , Shilong FAN , Zeyang LEI , Bingjin CHEN , Siqi BAO , Hua WU
IPC: G06N3/0475
Abstract: A method for evaluating a large model, an electronic device and a computer readable storage medium are provided, which relate to a field of artificial intelligence technology, and in particular to fields of large models technology and deep learning technology. The method includes: evaluating a response information of each of M large language models for an input instruction based on a preset evaluation rule, so as to obtain a first evaluation information for each response information, where M is a positive integer greater than 1; evaluating, in response to the first evaluation information for the M large language models being consistent with each other, each response information in a plurality of evaluation dimensions, so as to obtain a second evaluation information for each response information; and determining an evaluation result representing a responsiveness of each large language model, according to the second evaluation information for each response information.
-
-
-
Search Results
4
records
(took 0.019 seconds)
