SMILE - Semantic Modelling of Intent through Large-language Evaluations

SMILE项目旨在利用Overtone多年来一直在研究的自然语言处理技术，并进一步为内容企业和那些依赖内容的人创造一种新的方式来理解为什么一件作品的表现是这样的。它将创建一个音调分类器的原型，该原型采用大型语言模型并对其进行微调，以对一篇文章是幽默、严肃还是积极，以及其他可能影响文章如何与观众产生共鸣的定性方面产生细微的理解。这个项目将通过解决出版商最迫切的需求之一——新闻回避，帮助增加Overtone的服务。随着观众对反复报道的创伤性事件避而远之，新闻回避现象越来越严重。Overtone的模式将允许出版商优化他们的新闻交付，既包括重要、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，以满足他们的启发或娱乐需求。

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.