classification system. The manual work involved in processing and classifying occupational descriptions is error-prone, tedious, and … time-consuming. We finetune a preexisting language model (CANINE) to do this automatically, thereby performing in seconds …

We fine-tune a large language model to classify accounting topics within financial disclosures. This allows for the … efficient and accurate classification of accounting topics in large volumes of out-of-sample unlabeled text. Specifically, our … model leverages innovations in supervised machine learning and large language models to overcome the challenges of manually …

, large language models (LLMs) such as GPT 3.5 show a consistently good performance across all datasets, with accuracy rates … intelligence (AI) can play in facilitating product classification at scale and, more generally, in enhancing the categorization of …

propose a new methodology to automate patent classification. We contrast existing taxonomies with our own upon a widely used … patent dataset. In a regression analysis of patent classes upon patent characteristics, we show that classification bias …

the classic empirical asset pricing problem as a machine learningclassification problem. We construct classification …

actual meaning and definition of the skills. It allows for the classification of more than 17 000 unique skill keywords … contained in the Burning Glass dataset into 61 categories. The outcome of the classification exercise is validated using O … literature. Compared to a manual classification, the proposed approach organises large amounts of skills information in an …