Application of Large Language Models in Assessing Inventive Step in Patent Examination
With the rapid development of artificial intelligence technology,large language models have acquired high-quality natural language processing and logical reasoning capabilities.This paper,through case analysis,validates the effectiveness of large language models in the three-step method for assessing inventive step in patent examination.This includes identifying the closest prior art,recognizing the distinguishing features of the invention and the technical problem it solves,and evaluating the obviousness of the invention.Based on the performance of large language models in the aforementioned cases,the paper explores the advantages of using large language models in assessing inventive step during patent examination.It concludes that the application of large language models can enhance the efficiency and quality of patent examination and promote the standardization and objectivity of patent examination.
large language modelspatent examinationinventivenessobviousnesstraining data
NETL
NSTL
万方数据
