公开(公告)号：US20220108204A1

公开(公告)日：2022-04-07

申请号：US17061355

申请日：2020-10-01

Applicant: Google LLC

Inventor： Xianzhi Du ,  Yin Cui ,  Tsung-Yi Lin ,  Quoc V. Le ,  Pengchong Jin ,  Mingxing Tan ,  Golnaz Ghiasi ,  Xiaodan Song

IPC: G06N20/00 ,  G06N3/04 ,  G06F11/34

Abstract: A computer-implemented method of generating scale-permuted models can generate models having improved accuracy and reduced evaluation computational requirements. The method can include defining, by a computing system including one or more computing devices, a search space including a plurality of candidate permutations of a plurality of candidate feature blocks, each of the plurality of candidate feature blocks having a respective scale. The method can include performing, by the computing system, a plurality of search iterations by a search algorithm to select a scale-permuted model from the search space, the scale-permuted model based at least in part on a candidate permutation of the plurality of candidate permutations.

公开(公告)号：US20240282131A1

公开(公告)日：2024-08-22

申请号：US18421672

申请日：2024-01-24

Applicant: Google LLC

Inventor： Jie Ren ,  Zhe Liu ,  James Urquhart Allingham ,  Michael Ward Dusenberry ,  Dustin Tran ,  Yin Cui ,  Balaji Lakshminarayanan ,  Xiuye Gu

IPC: G06V20/70 ,  G06F40/40 ,  G06V10/74 ,  G06V10/764 ,  G06V10/776

CPC classification number: G06V20/70 ,  G06F40/40 ,  G06V10/761 ,  G06V10/764 ,  G06V10/776

Abstract: Systems and methods for zero-shot prompt ensembling for zero-shot classification with text-image models can include utilizing a pre-trained text-image model to perform downstream tasks based on prompt-based weighting. The systems and methods may adjust for frequency-based bias and may automatically determine different prompt associations with a given downstream task. The systems and methods can aggregate weighted text embeddings and then determine a classification output based on similarity measures between an image embedding and the aggregated weighted text embeddings.

公开(公告)号：US20240378509A1

公开(公告)日：2024-11-14

申请号：US18784068

申请日：2024-07-25

Applicant: Google LLC

Inventor： Xianzhi Du ,  Yin Cui ,  Tsung-Yi Lin ,  Quoc V. Le ,  Pengchong Jin ,  Mingxing Tan ,  Golnaz Ghiasi ,  Xiaodan Song

IPC: G06N20/00 ,  G06F11/34 ,  G06N3/04

Abstract: A computer-implemented method of generating scale-permuted models can generate models having improved accuracy and reduced evaluation computational requirements. The method can include defining, by a computing system including one or more computing devices, a search space including a plurality of candidate permutations of a plurality of candidate feature blocks, each of the plurality of candidate feature blocks having a respective scale. The method can include performing, by the computing system, a plurality of search iterations by a search algorithm to select a scale-permuted model from the search space, the scale-permuted model based at least in part on a candidate permutation of the plurality of candidate permutations.

公开(公告)号：US20240362460A1

公开(公告)日：2024-10-31

申请号：US18626833

申请日：2024-04-04

Applicant: Google LLC

Inventor： Li Zhang ,  Yandong Li ,  Yin Cui ,  Hong-You Chen ,  Mingda Zhang

IPC: G06N3/0455 ,  G06N3/084

CPC classification number: G06N3/0455 ,  G06N3/084

Abstract: The technology relates to providing personalized neural network-based models according to user input, which can be generated upon request or otherwise as needed. This may include receiving, by one or more processors of a computing device, input corresponding to a task description. Then the input corresponding to the task description is encoded into a set of text embeddings. Based on this, the system applies mixer prediction to the set of text embeddings to generate a set of mixers and learns a set of basis models according to the set of mixers. The set of basis models are combined to form a single personalized model corresponding to the task description. This personalized model can then be used in video understanding, quality assessment, providing a recommendation, performing a classification, or performing a search.

公开(公告)号：US12079695B2

公开(公告)日：2024-09-03

申请号：US17061355

申请日：2020-10-01

Applicant: Google LLC

Inventor： Xianzhi Du ,  Yin Cui ,  Tsung-Yi Lin ,  Quoc V. Le ,  Pengchong Jin ,  Mingxing Tan ,  Golnaz Ghiasi ,  Xiaodan Song

IPC: G06N20/00 ,  G06F11/34 ,  G06N3/04

CPC classification number: G06N20/00 ,  G06F11/3495 ,  G06N3/04

Abstract: A computer-implemented method of generating scale-permuted models can generate models having improved accuracy and reduced evaluation computational requirements. The method can include defining, by a computing system including one or more computing devices, a search space including a plurality of candidate permutations of a plurality of candidate feature blocks, each of the plurality of candidate feature blocks having a respective scale. The method can include performing, by the computing system, a plurality of search iterations by a search algorithm to select a scale-permuted model from the search space, the scale-permuted model based at least in part on a candidate permutation of the plurality of candidate permutations.