SMILE - Semantic Modelling of Intent through Large-language Evaluations

SMILE项目旨在利用Overtone多年来一直致力于的自然语言处理技术的进步，并进一步为内容企业和那些依赖内容来理解为什么作品表现如此出色的人创造一种新的方式。它将创建一个音调分类器的原型，该分类器采用大型语言模型并对其进行微调，以创建对作品是否幽默，严肃或积极的细微理解，以及其他可能影响文章如何与观众产生共鸣的定性方面。 这个项目将有助于增加泛音的提供解决一个最紧迫的需求，为出版商，新闻回避。随着观众对创伤性事件的反复报道避而不谈，新闻回避现象越来越多。Overtone的模式将使出版商能够优化新闻的传递，既包括对重要、严肃事件的报道，又确保为受众提供更轻松、更个性化的新闻，满足他们的灵感或娱乐需求。

The SMILE project aims to take advances in Natural Language Processing on which Overtone has been working for years and take them even further to create a new way for content businesses and those who rely on content to understand why a piece performs as it does. It will create a prototype of a tone classifier that takes large language models and fine-tunes them to create nuanced understanding of whether a piece is humorous, serious, or positive, as well as other qualitative aspects that can impact how an article resonates with an audience. This project will help add to Overtone's offering by addressing one of the most pressing needs for publishers, news avoidance. News avoidance has been growing as audiences turn away from the repeated coverage of traumatic events. Overtone's models will allow publishers to optimise the delivery of their news to include both coverage of important, serious events while ensuring that audiences also are served lighter, more personal news that fulfils their needs to be inspired or entertained.