The Effectiveness of Bidirectional Generative Patent Language Models

Jieh Sheng Lee*

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Generative patent language models can assist humans to write patent text more effectively. The question is how to measure effectiveness from a human-centric perspective and how to improve effectiveness. In this manuscript, a simplified design of the autocomplete function is proposed to increase effectiveness by more than 10%. With the simplified design, the effectiveness of autocomplete can reach more than 60%, which means that more than 60% of keystrokes can be saved by autocomplete. Since writing patent text does not necessarily start from the beginning to the end, a question is whether the generative model can assist a user no matter where to start writing. To answer the question, the generative models in this manuscript are pre-trained with training data in both directions. The generative models become bidirectional. Since text generation is bidirectional, the calculation of autocomplete effectiveness can be bidirectional and starts from anywhere in the text. After thorough experiments, a key finding is that the autocomplete effectiveness of a model for the same text remains similar no matter where the calculation starts. The finding indicates that such bidirectional models can assist a user at a similar level, no matter where the user starts to write.

原文English
主出版物標題Legal Knowledge and Information Systems - JURIX 2022
主出版物子標題The 35th Annual Conference
編輯Enrico Francesconi, Georg Borges, Christoph Sorge
發行者IOS Press BV
頁面194-199
頁數6
ISBN(電子)9781643683645
DOIs
出版狀態Published - 5 12月 2022
事件35th International Conference on Legal Knowledge and Information Systems, JURIX 2022 - Saarbrucken, Germany
持續時間: 14 12月 202216 12月 2022

出版系列

名字Frontiers in Artificial Intelligence and Applications
362
ISSN(列印)0922-6389
ISSN(電子)1879-8314

Conference

Conference35th International Conference on Legal Knowledge and Information Systems, JURIX 2022
國家/地區Germany
城市Saarbrucken
期間14/12/2216/12/22

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