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20182024
most citedDesign of Negative Sampling Strategies for Distantly Supervised Skill Extraction

6 citations · 20 across the 15 of their papers we have counts for

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cs.CL20222 cited

BioLORD: Learning Ontological Representations from Definitions (for Biomedical Concepts and their Textual Descriptions)

François Remy, Kris Demuynck, Thomas Demeester

This work introduces BioLORD, a new pre-training strategy for producing meaningful representations for clinical sentences and biomedical concepts. State-of-the-art methodologies op…

cs.CL2022

Robustifying Sentiment Classification by Maximally Exploiting Few Counterfactuals

Maarten De Raedt, Fréderic Godin, Chris Develder +1

For text classification tasks, finetuned language models perform remarkably well. Yet, they tend to rely on spurious patterns in training data, thus limiting their performance on o…

cs.CL2022

EduQG: A Multi-format Multiple Choice Dataset for the Educational Domain

Amir Hadifar, Semere Kiros Bitew, Johannes Deleu +2

We introduce a high-quality dataset that contains 3,397 samples comprising (i) multiple choice questions, (ii) answers (including distractors), and (iii) their source documents, fr…

cs.CL20226 cited

Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction

Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu +2

Skills play a central role in the job market and many human resources (HR) processes. In the wake of other digital experiences, today's online job market has candidates expecting t…

cs.CL20213 cited

JobBERT: Understanding Job Titles through Skills

Jens-Joris Decorte, Jeroen Van Hautte, Thomas Demeester +1

Job titles form a cornerstone of today's human resources (HR) processes. Within online recruitment, they allow candidates to understand the contents of a vacancy at a glance, while…

cs.CL2021

Injecting Knowledge Base Information into End-to-End Joint Entity and Relation Extraction and Coreference Resolution

Severine Verlinden, Klim Zaporojets, Johannes Deleu +2

We consider a joint information extraction (IE) model, solving named entity recognition, coreference resolution and relation extraction jointly over the whole document. In particul…