公开(公告)号：USD1073240S1

公开(公告)日：2025-04-29

申请号：US29987773

申请日：2025-01-27

Applicant: Rui Cheng

Designer： Rui Cheng

公开(公告)号：USD1073241S1

公开(公告)日：2025-04-29

申请号：US29987798

申请日：2025-01-27

Applicant: Rui Cheng

Designer： Rui Cheng

公开(公告)号：US12175206B2

公开(公告)日：2024-12-24

申请号：US17821227

申请日：2022-08-22

Applicant: Tianxiong Xiao ,  Rui Cheng ,  Bin Dong ,  Shanshan Jiang ,  Jiashi Zhang

Inventor： Tianxiong Xiao ,  Rui Cheng ,  Bin Dong ,  Shanshan Jiang ,  Jiashi Zhang

IPC: G06F40/30 ,  G06F16/33 ,  G06F16/332 ,  G06F40/205 ,  G06F40/40 ,  G06F40/47 ,  G06F40/56 ,  G06N3/0455 ,  G06N5/02 ,  G06N7/00

Abstract: A method and an apparatus for machine reading comprehension, and a non-transitory computer-readable recording medium are provided. In the method, a paragraph-question pair is obtained, and subword vectors corresponding to subwords in the paragraph-question pair are generated. Then, for each subword, relative positions of the subword with respect to the other subwords are determined based on distances, and self-attention information of the subword in a first part and mutual attention information of the subword in a second part are calculated by using the relative positions and the subword vector. Then, a fusion vector of the subword is generated based on the self-attention information and the mutual attention information. Then, the fusion vectors of the subwords are input to a decoder of a machine reading comprehension model so as to obtain an answer predicted by the decoder.

公开(公告)号：US12197479B2

公开(公告)日：2025-01-14

申请号：US18390496

申请日：2023-12-20

Applicant: Rui Cheng ,  Bin Dong ,  Shanshan Jiang ,  Lu Luo ,  Lei Ding

Inventor： Rui Cheng ,  Bin Dong ,  Shanshan Jiang ,  Lu Luo ,  Lei Ding

IPC: G06F16/33 ,  G06N3/045

Abstract: Disclosed are a semantic matching and retrieval method and apparatus. The semantic matching and retrieval method includes steps of obtaining both the vector representation of a query text and the vector representation of a document text; obtaining the final vector representation of the query text; obtaining the final vector representation of the document text; calculating, based on the final vector representation of the query text and the final vector representation of the document text, the similarity score between the query text and the document text; and selecting, based on the similarity scores between the query text and a plurality of document texts, a document text matching the query text from the plurality of document texts.