公开(公告)号：US20250045619A1

公开(公告)日：2025-02-06

申请号：US18228569

申请日：2023-07-31

Applicant: Maplebear Inc.

Inventor： Jin Zhang ,  Trace Levinson

IPC: G06N20/00

Abstract: A computing system uses a conditional loss function to train a multitask model. A conditional loss function is a loss function whose output is conditional on which branch's output the conditional loss function is scoring. Specifically, when the conditional loss function is applied to an output score generated by a branch whose corresponding task is not relevant to the training example for the output score, the conditional loss function generates a loss score that, when used in backpropagation, does not significantly change the parameters of the multitask model. The computing system uses conditional loss functions to generate a loss score for each output score generated by applying a multitask model to features of a set of training examples. If the task indicators indicate that the branch task is not relevant to the training example, the conditional loss function outputs a loss score of zero.