450 citations · 575 across the 28 of their papers we have counts for
20 papers · 1 filter
Career Path Prediction using Resume Representation Learning and Skill-based Matching
Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu +2
The impact of person-job fit on job satisfaction and performance is widely acknowledged, which highlights the importance of providing workers with next steps at the right time in t…
Distractor generation for multiple-choice questions with predictive prompting and large language models
Semere Kiros Bitew, Johannes Deleu, Chris Develder +1
Large Language Models (LLMs) such as ChatGPT have demonstrated remarkable performance across various tasks and have garnered significant attention from both researchers and practit…
Extreme Multi-Label Skill Extraction Training using Large Language Models
Jens-Joris Decorte, Severine Verlinden, Jeroen Van Hautte +3
Online job ads serve as a valuable source of information for skill requirements, playing a crucial role in labor market analysis and e-recruitment processes. Since such ads are typ…
Learning from Partially Annotated Data: Example-aware Creation of Gap-filling Exercises for Language Learning
Semere Kiros Bitew, Johannes Deleu, A. Seza Doğruöz +2
Since performing exercises (including, e.g., practice tests) forms a crucial component of learning, and creating such exercises requires non-trivial effort from the teacher, there…
BioDEX: Large-Scale Biomedical Adverse Drug Event Extraction for Real-World Pharmacovigilance
Karel D'Oosterlinck, François Remy, Johannes Deleu +7
Timely and accurate extraction of Adverse Drug Events (ADE) from biomedical literature is paramount for public safety, but involves slow and costly manual labor. We set out to impr…
TempEL: Linking Dynamically Evolving and Newly Emerging Entities
Klim Zaporojets, Lucie-Aimee Kaffee, Johannes Deleu +3
In our continuously evolving world, entities change over time and new, previously non-existing or unknown, entities appear. We study how this evolutionary scenario impacts the perf…
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…
Learning to Reuse Distractors to support Multiple Choice Question Generation in Education
Semere Kiros Bitew, Amir Hadifar, Lucas Sterckx +3
Multiple choice questions (MCQs) are widely used in digital learning systems, as they allow for automating the assessment process. However, due to the increased digital literacy of…
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…
CookDial: A dataset for task-oriented dialogs grounded in procedural documents
Yiwei Jiang, Klim Zaporojets, Johannes Deleu +2
This work presents a new dialog dataset, CookDial, that facilitates research on task-oriented dialog systems with procedural knowledge understanding. The corpus contains 260 human-…
Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution
Klim Zaporojets, Johannes Deleu, Yiwei Jiang +2
We consider the task of document-level entity linking (EL), where it is important to make consistent decisions for entity mentions over the full document jointly. We aim to leverag…
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…
DWIE: an entity-centric dataset for multi-task document-level information extraction
Klim Zaporojets, Johannes Deleu, Chris Develder +1
This paper presents DWIE, the 'Deutsche Welle corpus for Information Extraction', a newly created multi-task dataset that combines four main Information Extraction (IE) annotation…
Solving Arithmetic Word Problems by Scoring Equations with Recursive Neural Networks
Klim Zaporojets, Giannis Bekoulis, Johannes Deleu +2
Solving arithmetic word problems is a cornerstone task in assessing language understanding and reasoning capabilities in NLP systems. Recent works use automatic extraction and rank…
Sub-event detection from Twitter streams as a sequence labeling problem
Giannis Bekoulis, Johannes Deleu, Thomas Demeester +1
This paper introduces improved methods for sub-event detection in social media streams, by applying neural sequence models not only on the level of individual posts, but also direc…
Adversarial training for multi-context joint entity and relation extraction
Giannis Bekoulis, Johannes Deleu, Thomas Demeester +1
Adversarial training (AT) is a regularization method that can be used to improve the robustness of neural network methods by adding small perturbations in the training data. We sho…
Prior Attention for Style-aware Sequence-to-Sequence Models
Lucas Sterckx, Johannes Deleu, Chris Develder +1
We extend sequence-to-sequence models with the possibility to control the characteristics or style of the generated output, via attention that is generated a priori (before decodin…
Joint entity recognition and relation extraction as a multi-head selection problem
Giannis Bekoulis, Johannes Deleu, Thomas Demeester +1
State-of-the-art models for joint entity recognition and relation extraction strongly rely on external natural language processing (NLP) tools such as POS (part-of-speech) taggers…
An attentive neural architecture for joint segmentation and parsing and its application to real estate ads
Giannis Bekoulis, Johannes Deleu, Thomas Demeester +1
In processing human produced text using natural language processing (NLP) techniques, two fundamental subtasks that arise are (i) segmentation of the plain text into meaningful sub…
Knowledge Base Population using Semantic Label Propagation
Lucas Sterckx, Thomas Demeester, Johannes Deleu +1
A crucial aspect of a knowledge base population system that extracts new facts from text corpora, is the generation of training data for its relation extractors. In this paper, we…