31 citations · 116 across the 43 of their papers we have counts for
14 papers · 1 filter
Distributional Reinforcement Learning-based Energy Arbitrage Strategies in Imbalance Settlement Mechanism
Seyed Soroush Karimi Madahi, Bert Claessens, Chris Develder
Growth in the penetration of renewable energy sources makes supply more uncertain and leads to an increase in the system imbalance. This trend, together with the single imbalance p…
Demand response for residential building heating: Effective Monte Carlo Tree Search control based on physics-informed neural networks
Fabio Pavirani, Gargya Gokhale, Bert Claessens +1
To reduce global carbon emissions and limit climate change, controlling energy consumption in buildings is an important piece of the puzzle. Here, we specifically focus on using a…
Flexible Model Interpretability through Natural Language Model Editing
Karel D'Oosterlinck, Thomas Demeester, Chris Develder +1
Model interpretability and model editing are crucial goals in the age of large language models. Interestingly, there exists a link between these two goals: if a method is able to s…
Zero-Shot Cross-Lingual Sentiment Classification under Distribution Shift: an Exploratory Study
Maarten De Raedt, Semere Kiros Bitew, Fréderic Godin +2
The brittleness of finetuned language model performance on out-of-distribution (OOD) test samples in unseen domains has been well-studied for English, yet is unexplored for multi-l…
Personality Style Recognition via Machine Learning: Identifying Anaclitic and Introjective Personality Styles from Patients' Speech
Semere Kiros Bitew, Vincent Schelstraete, Klim Zaporojets +3
In disentangling the heterogeneity observed in psychopathology, personality of the patients is considered crucial. While it has been demonstrated that personality traits are reflec…
Transfer Learning in Transformer-Based Demand Forecasting For Home Energy Management System
Gargya Gokhale, Jonas Van Gompel, Bert Claessens +1
Increasingly, homeowners opt for photovoltaic (PV) systems and/or battery storage to minimize their energy bills and maximize renewable energy usage. This has spurred the developme…
Real-World Implementation of Reinforcement Learning Based Energy Coordination for a Cluster of Households
Gargya Gokhale, Niels Tiben, Marie-Sophie Verwee +3
Given its substantial contribution of 40\% to global power consumption, the built environment has received increasing attention to serve as a source of flexibility to assist the mo…
CAW-coref: Conjunction-Aware Word-level Coreference Resolution
Karel D'Oosterlinck, Semere Kiros Bitew, Brandon Papineau +3
State-of-the-art coreference resolutions systems depend on multiple LLM calls per document and are thus prohibitively expensive for many use cases (e.g., information extraction wit…
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…
IDAS: Intent Discovery with Abstractive Summarization
Maarten De Raedt, Fréderic Godin, Thomas Demeester +1
Intent discovery is the task of inferring latent intents from a set of unlabeled utterances, and is a useful step towards the efficient creation of new conversational agents. We sh…
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…