activity
20192023
most citedLarge Language Models in the Workplace: A Case Study on Prompt Engineering for Job Type Classification

20 citations · 50 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2023★ 6 cited

Large Language Models as Batteries-Included Zero-Shot ESCO Skills Matchers

Benjamin Clavié, Guillaume Soulié

Understanding labour market dynamics requires accurately identifying the skills required for and possessed by the workforce. Automation techniques are increasingly being developed…

cs.CL2023★ 20 cited

Large Language Models in the Workplace: A Case Study on Prompt Engineering for Job Type Classification

Benjamin Clavié, Alexandru Ciceu, Frederick Naylor +2

This case study investigates the task of job classification in a real-world setting, where the goal is to determine whether an English-language job posting is appropriate for a gra…

cs.CL2021★ 2 cited

The Unreasonable Effectiveness of the Baseline: Discussing SVMs in Legal Text Classification

Benjamin Clavié, Marc Alphonsus

We aim to highlight an interesting trend to contribute to the ongoing debate around advances within legal Natural Language Processing. Recently, the focus for most legal text class…

cs.CL2021★ 3 cited

LegaLMFiT: Efficient Short Legal Text Classification with LSTM Language Model Pre-Training

Benjamin Clavié, Akshita Gheewala, Paul Briton +3

Large Transformer-based language models such as BERT have led to broad performance improvements on many NLP tasks. Domain-specific variants of these models have demonstrated excell…

cs.CY2019★ 19 cited

EduBERT: Pretrained Deep Language Models for Learning Analytics

Benjamin Clavié, Kobi Gal

The use of large pretrained neural networks to create contextualized word embeddings has drastically improved performance on several natural language processing (NLP) tasks. These…