Search Results for author: Chris Develder

Found 38 papers, 20 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.

Passage Retrieval Response Generation +1

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 +1

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).

Sentiment Analysis Sentiment Classification +2

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

no code implementations12 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 +2

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.

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.

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 Coreference Resolution +5

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.

 Ranked #1 on Coreference Resolution on DWIE (Avg. F1 metric)

coreference-resolution Coreference Resolution +6

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.

Deep Clustering Sentence Embedding +2

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

Definition and evaluation of model-free coordination of electrical vehicle charging with reinforcement learning

no code implementations27 Sep 2018 Nasrin Sadeghianpourhamami, Johannes Deleu, Chris Develder

In this paper, we propose a new Markov decision process (MDP) formulation in the RL framework, to jointly coordinate a set of EV charging stations.

reinforcement-learning reinforcement Learning

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

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

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.


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

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