31 citations · 116 across the 43 of their papers we have counts for
43 papers
Agent Collectives Should Not Detect Their Own Imposters: A Chess Case Study
Alexandre Le Mercier, Chris Develder, Thomas Demeester
A collective of AI agents collaborating on a task has the potential to outclass any individual agent for that task. We study the robustness of such collectives against possible imp…
CLASP: Defending Hybrid Large Language Models Against Hidden State Poisoning Attacks
Alexandre Le Mercier, Thomas Demeester, Chris Develder
State space models (SSMs) like Mamba have gained significant traction as efficient alternatives to Transformers, achieving linear complexity while maintaining competitive performan…
Hidden State Poisoning Attacks against Mamba-based Language Models
Alexandre Le Mercier, Chris Develder, Thomas Demeester
State space models (SSMs) like Mamba offer efficient alternatives to Transformer-based language models, with linear time complexity. Yet, their adversarial robustness remains criti…
Efficient Text Encoders for Labor Market Analysis
Jens-Joris Decorte, Jeroen Van Hautte, Chris Develder +1
Labor market analysis relies on extracting insights from job advertisements, which provide valuable yet unstructured information on job titles and corresponding skill requirements.…
Gaming Strategies in European Imbalance Settlement Mechanisms
Seyed Soroush Karimi Madahi, Kenneth Bruninx, Bert Claessens +1
Transmission System Operators (TSOs) rely on balancing energy provided by Balancing Service Providers (BSPs) to maintain the supply-demand balance in real time. Balance Responsible…
Single- vs. Dual-Prompt Dialogue Generation with LLMs for Job Interviews in Human Resources
Joachim De Baer, A. Seza Doğruöz, Thomas Demeester +1
Optimizing language models for use in conversational agents requires large quantities of example dialogues. Increasingly, these dialogues are synthetically generated by using power…
Predicting and Publishing Accurate Imbalance Prices Using Monte Carlo Tree Search
Fabio Pavirani, Jonas Van Gompel, Seyed Soroush Karimi Madahi +2
The growing reliance on renewable energy sources, particularly solar and wind, has introduced challenges due to their uncontrollable production. This complicates maintaining the el…
On the Biased Assessment of Expert Finding Systems
Jens-Joris Decorte, Jeroen Van Hautte, Chris Develder +1
In large organisations, identifying experts on a given topic is crucial in leveraging the internal knowledge spread across teams and departments. So-called enterprise expert retrie…
SkillMatch: Evaluating Self-supervised Learning of Skill Relatedness
Jens-Joris Decorte, Jeroen Van Hautte, Thomas Demeester +1
Accurately modeling the relationships between skills is a crucial part of human resources processes such as recruitment and employee development. Yet, no benchmarks exist to evalua…
Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment
Karel D'Oosterlinck, Winnie Xu, Chris Develder +5
Large Language Models (LLMs) are often aligned using contrastive alignment objectives and preference pair datasets. The interaction between model, paired data, and objective makes…
Control Policy Correction Framework for Reinforcement Learning-based Energy Arbitrage Strategies
Seyed Soroush Karimi Madahi, Gargya Gokhale, Marie-Sophie Verwee +2
A continuous rise in the penetration of renewable energy sources, along with the use of the single imbalance pricing, provides a new opportunity for balance responsible parties to…
HomeLabGym: A real-world testbed for home energy management systems
Toon Van Puyvelde, Marie-Sophie Verwee, Gargya Gokhale +2
Amid growing environmental concerns and resulting energy costs, there is a rising need for efficient Home Energy Management Systems (HEMS). Evaluating such innovative HEMS solution…
Probabilistic forecasting of power system imbalance using neural network-based ensembles
Jonas Van Gompel, Bert Claessens, Chris Develder
Keeping the balance between electricity generation and consumption is becoming increasingly challenging and costly, mainly due to the rising share of renewables, electric vehicles…
Explainable Reinforcement Learning-based Home Energy Management Systems using Differentiable Decision Trees
Gargya Gokhale, Bert Claessens, Chris Develder
With the ongoing energy transition, demand-side flexibility has become an important aspect of the modern power grid for providing grid support and allowing further integration of s…
Distill2Explain: Differentiable decision trees for explainable reinforcement learning in energy application controllers
Gargya Gokhale, Seyed Soroush Karimi Madahi, Bert Claessens +1
Demand-side flexibility is gaining importance as a crucial element in the energy transition process. Accounting for about 25% of final energy consumption globally, the residential…
In-Context Learning for Extreme Multi-Label Classification
Karel D'Oosterlinck, Omar Khattab, François Remy +3
Multi-label classification problems with thousands of classes are hard to solve with in-context learning alone, as language models (LMs) might lack prior knowledge about the precis…
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…