场景化语言模型

依托大规模语言模型，在此基础上做迁移学习，结合政务行业的数据做自适应的再训练，从而获得更好的文本语义表征能力，使得模型能够结合上下文更好的理解整体语义。为下游各个业务场景的任务提供一个高性能、高准确的语义向量映射模型。Built upon large language models, this work first conducts transfer learning, then performs adaptive retraining with government sector data to enhance text semantic representation capabilities. This allows the model to better comprehend overall semantics by leveraging contextual information, thus providing a high-performance and highly accurate semantic vector mapping model for tasks across various downstream business scenarios.

搜集汇总

背景与挑战

背景概述

该数据集基于大规模语言模型，通过政务行业数据迁移学习优化语义表征能力，为下游任务提供高精度语义理解支持。其核心价值在于结合行业场景提升上下文语义理解性能。