公开(公告)号：US20250061339A1

公开(公告)日：2025-02-20

申请号：US18936628

申请日：2024-11-04

Applicant: Lemon Inc.

Inventor： Andrew Estornell ,  Jean-Francois Ton ,  Yuanshun Yao ,  Yang Liu

IPC: G06N3/092 ,  G06F40/40

Abstract: Embodiments of the present disclosure provide a solution for model training. A method comprises: performing training of a critic model and training of an actor model according to an alternating scheme. The actor model is configured to generate a response for an input question based on a feedback generated by the critic model, and the critic model is configured to generate a feedback to a response generated by the actor mode.

公开(公告)号：US20250005459A1

公开(公告)日：2025-01-02

申请号：US18885135

申请日：2024-09-13

Applicant: Lemon Inc.

Inventor： Yuanshun Yao ,  Jiaheng Wei ,  Jean-Francois Ton ,  Hongyi Guo ,  Andrew Estornell ,  Yang Liu

IPC: G06N20/00

Abstract: Embodiments of the disclosure provide a solution for machine learning model evaluation. The solution includes: obtaining a target answer to a test question generated by a target machine learning (ML) model; obtaining a plurality of reference answers to the test question generated respectively by a plurality of reference ML models; determining respective professional levels of the plurality of reference ML models in answering the test question; and generating an evaluation result on correctness of the target ML model in question answering based on the target answer, the plurality of reference answers and the respective professional levels of the plurality of reference ML models.