Trainieren von Generativen Neuronalen Netzwerksystemen unter Verwendung mehrerer Belohnungsmodelle

Details

Veröffentlichungs-Nr.

EP4787233

Anmeldetag

3. Februar 2026

Veröffentlichung

5. August 2026

Rechtsraum

EP

Abstract

Methods, systems, and computer storage media are provided for training generative neural network systems, such as Large Language Models (LLMs) or Vision-Language Models (VLMs), using multiple reward models. The process involves generating one or more output sequences from a training input sequence and processing these examples using a plurality of different reward models to generate respective reward values. These reward values are combined to obtain an aggregated reward, which may be calculated as a product of the values, a weighted geometric mean, or a Nash score. The generative neural network is trained using an objective function determined using the aggregated reward, such as a cross-entropy loss or a contrastive objective function, often utilizing log score differences between the system and a reference model. These techniques allow for multi-objective alignment and are adapted for implementation on parallel processing computer systems.

Anmelder

Firma

GDM Holding LLC

Land

🇺🇸 USA