Search Results for author: Chris Develder

Found 58 papers, 27 papers with code

UGent-T2K at the 2nd DialDoc Shared Task: A Retrieval-Focused Dialog System Grounded in Multiple Documents

no code implementations dialdoc (ACL) 2022 Yiwei Jiang, Amir Hadifar, Johannes Deleu, Thomas Demeester, Chris Develder

Further, error analysis reveals two major failure cases, to be addressed in future work: (i) in case of topic shift within the dialog, retrieval often fails to select the correct grounding document(s), and (ii) generation sometimes fails to use the correctly retrieved grounding passage.

Decoder Passage Retrieval +2

Control Policy Correction Framework for Reinforcement Learning-based Energy Arbitrage Strategies

no code implementations29 Apr 2024 Seyed Soroush Karimi Madahi, Gargya Gokhale, Marie-Sophie Verwee, Bert Claessens, Chris Develder

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 reduce their cost through energy arbitrage in the imbalance settlement mechanism.

Knowledge Distillation reinforcement-learning +1

Probabilistic forecasting of power system imbalance using neural network-based ensembles

no code implementations23 Apr 2024 Jonas Van Gompel, Bert Claessens, Chris Develder

Each minute, our model predicts the imbalance of the current and upcoming two quarter-hours, along with uncertainty estimations on these forecasts.

Variable Selection

HomeLabGym: A real-world testbed for home energy management systems

no code implementations22 Apr 2024 Toon Van Puyvelde, Marie-Sophie Verwee, Gargya Gokhale, Mehran Zareh Eshghdoust, Chris Develder

We present an overview of HomeLabGym, and demonstrate its usefulness to researchers in a comparison between real-world and simulated environments in controlling a residential battery in response to real-time prices.

energy management Management +1

Explainable Reinforcement Learning-based Home Energy Management Systems using Differentiable Decision Trees

no code implementations18 Mar 2024 Gargya Gokhale, Bert Claessens, Chris Develder

We aim to address this challenging problem and introduce a reinforcement learning-based approach using differentiable decision trees.

energy management Management +1

In-Context Learning for Extreme Multi-Label Classification

2 code implementations22 Jan 2024 Karel D'Oosterlinck, Omar Khattab, François Remy, Thomas Demeester, Chris Develder, Christopher Potts

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 precise classes or how to assign them, and it is generally infeasible to demonstrate every class in a prompt.

Classification Extreme Multi-Label Classification +2

Distributional Reinforcement Learning-based Energy Arbitrage Strategies in Imbalance Settlement Mechanism

no code implementations23 Dec 2023 Seyed Soroush Karimi Madahi, Bert Claessens, Chris Develder

Our proposed control framework takes a risk-sensitive perspective, allowing BRPs to adjust their risk preferences: we aim to optimize a weighted sum of the arbitrage profit and a risk measure while constraining the daily number of cycles for the battery.

Distributional Reinforcement Learning Q-Learning +1

Demand response for residential building heating: Effective Monte Carlo Tree Search control based on physics-informed neural networks

no code implementations6 Dec 2023 Fabio Pavirani, Gargya Gokhale, Bert Claessens, Chris Develder

Here, we specifically focus on using a demand response (DR) algorithm to limit the energy consumption of a residential building's heating system while respecting user's thermal comfort.

Board Games Model Predictive Control +1

Zero-Shot Cross-Lingual Sentiment Classification under Distribution Shift: an Exploratory Study

no code implementations11 Nov 2023 Maarten De Raedt, Semere Kiros Bitew, Fréderic Godin, Thomas Demeester, Chris Develder

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-lingual models.

Cross-Lingual Sentiment Classification Sentiment Analysis +3

Real-World Implementation of Reinforcement Learning Based Energy Coordination for a Cluster of Households

no code implementations29 Oct 2023 Gargya Gokhale, Niels Tiben, Marie-Sophie Verwee, Manu Lahariya, Bert Claessens, Chris Develder

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 modern power grid.

energy management Reinforcement Learning (RL)

Transfer Learning in Transformer-Based Demand Forecasting For Home Energy Management System

no code implementations29 Oct 2023 Gargya Gokhale, Jonas Van Gompel, Bert Claessens, Chris Develder

Specifically, we train an advanced forecasting model (a temporal fusion transformer) using data from multiple different households, and then finetune this global model on a new household with limited data (i. e. only a few days).

energy management Load Forecasting +3

Career Path Prediction using Resume Representation Learning and Skill-based Matching

no code implementations24 Oct 2023 Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester

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 their career.

Representation Learning

CAW-coref: Conjunction-Aware Word-level Coreference Resolution

1 code implementation9 Oct 2023 Karel D'Oosterlinck, Semere Kiros Bitew, Brandon Papineau, Christopher Potts, Thomas Demeester, Chris Develder

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 with large corpora).

coreference-resolution

Distractor generation for multiple-choice questions with predictive prompting and large language models

1 code implementation30 Jul 2023 Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester

We also show the gains of our approach 1 in generating high-quality distractors by comparing it with a zero-shot ChatGPT and a few-shot ChatGPT prompted with static examples.

Distractor Generation Multiple-choice

Extreme Multi-Label Skill Extraction Training using Large Language Models

no code implementations20 Jul 2023 Jens-Joris Decorte, Severine Verlinden, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester

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.

Contrastive Learning Extreme Multi-Label Classification

Learning from Partially Annotated Data: Example-aware Creation of Gap-filling Exercises for Language Learning

1 code implementation2 Jun 2023 Semere Kiros Bitew, Johannes Deleu, A. Seza Doğruöz, Chris Develder, Thomas Demeester

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 is a great value in automatic exercise generation in digital tools in education.

IDAS: Intent Discovery with Abstractive Summarization

1 code implementation31 May 2023 Maarten De Raedt, Fréderic Godin, Thomas Demeester, Chris Develder

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.

Abstractive Text Summarization Descriptive +4

BioDEX: Large-Scale Biomedical Adverse Drug Event Extraction for Real-World Pharmacovigilance

1 code implementation22 May 2023 Karel D'Oosterlinck, François Remy, Johannes Deleu, Thomas Demeester, Chris Develder, Klim Zaporojets, Aneiss Ghodsi, Simon Ellershaw, Jack Collins, Christopher Potts

We introduce BioDEX, a large-scale resource for Biomedical adverse Drug Event Extraction, rooted in the historical output of drug safety reporting in the U. S. BioDEX consists of 65k abstracts and 19k full-text biomedical papers with 256k associated document-level safety reports created by medical experts.

Event Extraction

TempEL: Linking Dynamically Evolving and Newly Emerging Entities

1 code implementation5 Feb 2023 Klim Zaporojets, Lucie-Aimee Kaffee, Johannes Deleu, Thomas Demeester, Chris Develder, Isabelle Augenstein

For that study, we introduce TempEL, an entity linking dataset that consists of time-stratified English Wikipedia snapshots from 2013 to 2022, from which we collect both anchor mentions of entities, and these target entities' descriptions.

Entity Disambiguation Entity Linking

PhysQ: A Physics Informed Reinforcement Learning Framework for Building Control

no code implementations21 Nov 2022 Gargya Gokhale, Bert Claessens, Chris Develder

As a physics-informed reinforcement learning framework for building control, PhysQ forms a step in bridging the gap between conventional model-based control and data-intensive control based on reinforcement learning.

reinforcement-learning Reinforcement Learning (RL)

Learning to Reuse Distractors to support Multiple Choice Question Generation in Education

1 code implementation25 Oct 2022 Semere Kiros Bitew, Amir Hadifar, Lucas Sterckx, Johannes Deleu, Chris Develder, Thomas Demeester

This paper studies how a large existing set of manually created answers and distractors for questions over a variety of domains, subjects, and languages can be leveraged to help teachers in creating new MCQs, by the smart reuse of existing distractors.

Multiple-choice Question Generation +1

Robustifying Sentiment Classification by Maximally Exploiting Few Counterfactuals

1 code implementation21 Oct 2022 Maarten De Raedt, Fréderic Godin, Chris Develder, Thomas Demeester

We demonstrate the effectiveness of our approach in sentiment classification, using IMDb data for training and other sets for OOD tests (i. e., Amazon, SemEval and Yelp).

counterfactual Sentiment Analysis +3

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

1 code implementation12 Oct 2022 Amir Hadifar, Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester

Thus, our versatile dataset can be used for both question and distractor generation, as well as to explore new challenges such as question format conversion.

Distractor Generation Multiple-choice +3

Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction

1 code implementation13 Sep 2022 Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester

We introduce a manually annotated evaluation benchmark for skill extraction based on the ESCO taxonomy, on which we validate our models.

CookDial: A dataset for task-oriented dialogs grounded in procedural documents

1 code implementation17 Jun 2022 Yiwei Jiang, Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder

This work presents a new dialog dataset, CookDial, that facilitates research on task-oriented dialog systems with procedural knowledge understanding.

Decision Making Response Generation

Physics Informed LSTM Network for Flexibility Identification in Evaporative Cooling Systems

no code implementations19 May 2022 Manu Lahariya, Farzaneh Karami, Chris Develder, Guillaume Crevecoeur

These physics informed networks approximate the time-dependent relationship between control input and system response while enforcing the dynamics of the process in the neural network architecture.

BIG-bench Machine Learning

Optimized cost function for demand response coordination of multiple EV charging stations using reinforcement learning

no code implementations3 Mar 2022 Manu Lahariya, Nasrin Sadeghianpourhamami, Chris Develder

However, we note that the computationally expensive cost function adopted in the previous research leads to large training times, which limits the feasibility and practicality of the approach.

Reinforcement Learning (RL)

Defining a synthetic data generator for realistic electric vehicle charging sessions

1 code implementation28 Feb 2022 Manu Lahariya, Dries Benoit, Chris Develder

Addressing this need for publicly available and realistic data, we develop a synthetic data generator (SDG) for EV charging sessions.

Learning physics-informed simulation models for soft robotic manipulation: A case study with dielectric elastomer actuators

no code implementations25 Feb 2022 Manu Lahariya, Craig Innes, Chris Develder, Subramanian Ramamoorthy

We simulate the task of using DEA to pull a coin along a surface with frictional contact, using FEM, and evaluate the physics-informed model for simulation, control, and inference.

Physics Informed Neural Networks for Control Oriented Thermal Modeling of Buildings

1 code implementation23 Nov 2021 Gargya Gokhale, Bert Claessens, Chris Develder

To combine the interpretability of white/gray box physics models and the expressive power of neural networks, we propose a physics informed neural network approach for this modeling task.

Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution

1 code implementation ACL 2022 Klim Zaporojets, Johannes Deleu, Yiwei Jiang, Thomas Demeester, Chris Develder

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.

coreference-resolution Entity Linking +1

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

1 code implementation Findings (ACL) 2021 Severine Verlinden, Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder

The used KB entity representations are learned from either (i) hyperlinked text documents (Wikipedia), or (ii) a knowledge graph (Wikidata), and appear complementary in raising IE performance.

coreference-resolution Entity Linking +4

A Million Tweets Are Worth a Few Points: Tuning Transformers for Customer Service Tasks

1 code implementation NAACL 2021 Amir Hadifar, Sofie Labat, Véronique Hoste, Chris Develder, Thomas Demeester

In online domain-specific customer service applications, many companies struggle to deploy advanced NLP models successfully, due to the limited availability of and noise in their datasets.

DWIE: an entity-centric dataset for multi-task document-level information extraction

2 code implementations26 Sep 2020 Klim Zaporojets, Johannes Deleu, Chris Develder, Thomas Demeester

Second, the document-level multi-task annotations require the models to transfer information between entity mentions located in different parts of the document, as well as between different tasks, in a joint learning setting.

coreference-resolution Entity Linking +5

Solving Arithmetic Word Problems by Scoring Equations with Recursive Neural Networks

no code implementations11 Sep 2020 Klim Zaporojets, Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

Recent works use automatic extraction and ranking of candidate solution equations providing the answer to arithmetic word problems.

Block-wise Dynamic Sparseness

1 code implementation14 Jan 2020 Amir Hadifar, Johannes Deleu, Chris Develder, Thomas Demeester

In this paper, we present a new method for \emph{dynamic sparseness}, whereby part of the computations are omitted dynamically, based on the input.

Language Modelling

A Self-Training Approach for Short Text Clustering

1 code implementation WS 2019 Amir Hadifar, Lucas Sterckx, Thomas Demeester, Chris Develder

Short text clustering is a challenging problem when adopting traditional bag-of-words or TF-IDF representations, since these lead to sparse vector representations of the short texts.

Clustering Deep Clustering +4

Sub-event detection from Twitter streams as a sequence labeling problem

1 code implementation NAACL 2019 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

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 directly on the stream level.

Event Detection

Predefined Sparseness in Recurrent Sequence Models

1 code implementation CONLL 2018 Thomas Demeester, Johannes Deleu, Fréderic Godin, Chris Develder

Inducing sparseness while training neural networks has been shown to yield models with a lower memory footprint but similar effectiveness to dense models.

Language Modelling Word Embeddings

Adversarial training for multi-context joint entity and relation extraction

1 code implementation EMNLP 2018 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

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.

Joint Entity and Relation Extraction Relation

Prior Attention for Style-aware Sequence-to-Sequence Models

no code implementations25 Jun 2018 Lucas Sterckx, Johannes Deleu, Chris Develder, Thomas Demeester

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 decoding) from a latent code vector.

Lexical Simplification Sentence

Joint entity recognition and relation extraction as a multi-head selection problem

6 code implementations20 Apr 2018 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

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 and dependency parsers.

POS Relation

An attentive neural architecture for joint segmentation and parsing and its application to real estate ads

1 code implementation27 Sep 2017 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

In this work, we propose a new joint model that is able to tackle the two tasks simultaneously and construct the property tree by (i) avoiding the error propagation that would arise from the subtasks one after the other in a pipelined fashion, and (ii) exploiting the interactions between the subtasks.

Dependency Parsing

Reconstructing the house from the ad: Structured prediction on real estate classifieds

1 code implementation EACL 2017 Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder

In this paper, we address the (to the best of our knowledge) new problem of extracting a structured description of real estate properties from their natural language descriptions in classifieds.

Dependency Parsing Named Entity Recognition (NER) +1

Knowledge Base Population using Semantic Label Propagation

no code implementations19 Nov 2015 Lucas Sterckx, Thomas Demeester, Johannes Deleu, Chris Develder

We propose to combine distant supervision with minimal manual supervision in a technique called feature labeling, to eliminate noise from the large and noisy initial training set, resulting in a significant increase of precision.

Knowledge Base Population Relation

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