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ORCIDThomas Demeester
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- affiliation: Ghent University, Belgium
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2020 – today
- 2025
[j24]Ruben Janssens
, Pieter Wolfert, Thomas Demeester, Tony Belpaeme:
Integrating Visual Context Into Language Models for Situated Social Conversation Starters. IEEE Trans. Affect. Comput. 16(1): 223-236 (2025)- [d2]Paloma Rabaey, Stefan Heytens, Thomas Demeester:
SynSUM - Synthetic Benchmark with Structured and Unstructured Medical Records. IEEE DataPort, 2025
- [i75]Max Hallemeesch, Marija Pizurica, Paloma Rabaey, Olivier Gevaert, Thomas Demeester, Kathleen Marchal:
Prior Knowledge Injection into Deep Learning Models Predicting Gene Expression from Whole Slide Images. CoRR abs/2501.14056 (2025) - [i74]Joachim De Baer, A. Seza Dogruöz, Thomas Demeester, Chris Develder:
Single- vs. Dual-Prompt Dialogue Generation with LLMs for Job Interviews in Human Resources. CoRR abs/2502.18650 (2025) - 2024
- [j23]Yiwei Jiang, Maarten De Raedt, Johannes Deleu, Thomas Demeester, Chris Develder:
Few-shot out-of-scope intent classification: analyzing the robustness of prompt-based learning. Appl. Intell. 54(2): 1474-1496 (2024) - [j22]Maarten De Raedt, Fréderic Godin, Chris Develder, Thomas Demeester:
Revisiting clustering for efficient unsupervised dialogue structure induction. Appl. Intell. 54(7): 5278-5305 (2024) - [j21]François Remy, Kris Demuynck, Thomas Demeester:
BioLORD-2023: semantic textual representations fusing large language models and clinical knowledge graph insights. J. Am. Medical Informatics Assoc. 31(9): 1844-1855 (2024) - [j20]Sofie Labat, Thomas Demeester, Véronique Hoste:
EmoTwiCS: a corpus for modelling emotion trajectories in Dutch customer service dialogues on Twitter. Lang. Resour. Evaluation 58(2): 505-546 (2024) - [j19]Semere Kiros Bitew, Amir Hadifar, Lucas Sterckx, Johannes Deleu, Chris Develder, Thomas Demeester:
Learning to Reuse Distractors to Support Multiple-Choice Question Generation in Education. IEEE Trans. Learn. Technol. 17: 375-390 (2024) - [c69]Paloma Rabaey, Johannes Deleu, Stefan Heytens, Thomas Demeester:
Clinical Reasoning over Tabular Data and Text with Bayesian Networks. AIME (1) 2024: 229-250 - [c68]Jens-Joris Decorte, Jeroen Van Hautte, Chris Develder, Thomas Demeester:
On the Biased Assessment of Expert Finding Systems. HR@RecSys 2024 - [c67]Eva Verhelst, Ruben Janssens, Thomas Demeester, Tony Belpaeme:
Adaptive Second Language Tutoring Using Generative AI and a Social Robot. HRI (Companion) 2024: 1080-1084 - [c66]Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Johan Decruyenaere, Christiaan Polet, Thomas Demeester, Stijn Vansteelandt:
Debiasing Synthetic Data Generated by Deep Generative Models. NeurIPS 2024 - [c65]Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Stijn Vansteelandt, Thomas Demeester:
The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data. UAI 2024: 966-996 - [i73]Karel D'Oosterlinck, Omar Khattab, François Remy, Thomas Demeester, Chris Develder, Christopher Potts:
In-Context Learning for Extreme Multi-Label Classification. CoRR abs/2401.12178 (2024) - [i72]Henri Arno, Klaas Mulier, Joke Baeck, Thomas Demeester:
From Numbers to Words: Multi-Modal Bankruptcy Prediction Using the ECL Dataset. CoRR abs/2401.12652 (2024) - [i71]Paloma Rabaey, Johannes Deleu, Stefan Heytens, Thomas Demeester:
Clinical Reasoning over Tabular Data and Text with Bayesian Networks. CoRR abs/2403.09481 (2024) - [i70]François Remy, Pieter Delobelle, Hayastan Avetisyan, Alfiya Khabibullina, Miryam de Lhoneux, Thomas Demeester:
Trans-Tokenization and Cross-lingual Vocabulary Transfers: Language Adaptation of LLMs for Low-Resource NLP. CoRR abs/2408.04303 (2024) - [i69]Karel D'Oosterlinck, Winnie Xu, Chris Develder, Thomas Demeester, Amanpreet Singh, Christopher Potts, Douwe Kiela, Shikib Mehri:
Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment. CoRR abs/2408.06266 (2024) - [i68]Paloma Rabaey, Henri Arno, Stefan Heytens, Thomas Demeester:
SynSUM - Synthetic Benchmark with Structured and Unstructured Medical Records. CoRR abs/2409.08936 (2024) - [i67]Henri Arno, Paloma Rabaey, Thomas Demeester:
From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding. CoRR abs/2409.15503 (2024) - [i66]Jens-Joris Decorte, Jeroen Van Hautte, Thomas Demeester, Chris Develder:
SkillMatch: Evaluating Self-supervised Learning of Skill Relatedness. CoRR abs/2410.05006 (2024) - [i65]Jens-Joris Decorte, Jeroen Van Hautte, Chris Develder, Thomas Demeester:
On the Biased Assessment of Expert Finding Systems. CoRR abs/2410.05018 (2024) - [i64]Felix Koulischer, Johannes Deleu, Gabriel Raya, Thomas Demeester, Luca Ambrogioni:
Dynamic Negative Guidance of Diffusion Models. CoRR abs/2410.14398 (2024) - [i63]Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Thomas Demeester, Stijn Vansteelandt:
Debiasing Synthetic Data Generated by Deep Generative Models. CoRR abs/2411.04216 (2024) - [i62]Matthieu Meeus, Anthony Rathé, François Remy, Pieter Delobelle, Jens-Joris Decorte, Thomas Demeester:
ChocoLlama: Lessons Learned From Teaching Llamas Dutch. CoRR abs/2412.07633 (2024) - 2023
- [j18]Amir Hadifar, Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester:
EduQG: A Multi-Format Multiple-Choice Dataset for the Educational Domain. IEEE Access 11: 20885-20896 (2023) - [j17]Yiwei Jiang, Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder:
CookDial: a dataset for task-oriented dialogs grounded in procedural documents. Appl. Intell. 53(4): 4748-4766 (2023) - [c64]Semere Kiros Bitew, Johannes Deleu, A. Seza Dogruöz, Chris Develder, Thomas Demeester:
Learning from Partially Annotated Data: Example-aware Creation of Gap-filling Exercises for Language Learning. BEA@ACL 2023: 598-609 - [c63]François Remy, Kris Demuynck, Thomas Demeester:
Automatic Glossary of Clinical Terminology: a Large-Scale Dictionary of Biomedical Definitions Generated from Ontological Knowledge. BioNLP@ACL 2023: 265-272 - [c62]Amir Hadifar, Semere Kiros Bitew, Johannes Deleu, Véronique Hoste, Chris Develder, Thomas Demeester:
Diverse Content Selection for Educational Question Generation. EACL (Student Research Workshop) 2023: 123-133 - [c61]Karel D'Oosterlinck, François Remy, Johannes Deleu, Thomas Demeester, Chris Develder, Klim Zaporojets, Aneiss Ghodsi, Simon Ellershaw, Jack Collins, Christopher Potts:
BioDEX: Large-Scale Biomedical Adverse Drug Event Extraction for Real-World Pharmacovigilance. EMNLP (Findings) 2023: 13425-13454 - [c60]Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester:
Career Path Prediction using Resume Representation Learning and Skill-based Matching. HR@RecSys 2023 - [c59]François Remy, Alfiya Khabibullina, Thomas Demeester:
Detecting Idiomatic Multiword Expressions in Clinical Terminology using Definition-Based Representation Learning. MWE@EACL 2023: 73-80 - [c58]Quanqi Du, Sofie Labat, Thomas Demeester, Véronique Hoste:
Unimodalities Count as Perspectives in Multimodal Emotion Annotation. NLPerspectives@ECAI 2023 - [c57]Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester:
Distractor Generation for Multiple-Choice Questions with Predictive Prompting and Large Language Models. PKDD/ECML Workshops (2) 2023: 48-63 - [i61]Klim Zaporojets, Lucie-Aimée Kaffee, Johannes Deleu, Thomas Demeester, Chris Develder, Isabelle Augenstein:
TempEL: Linking Dynamically Evolving and Newly Emerging Entities. CoRR abs/2302.02500 (2023) - [i60]François Remy, Alfiya Khabibullina, Thomas Demeester:
Detecting Idiomatic Multiword Expressions in Clinical Terminology using Definition-Based Representation Learning. CoRR abs/2305.06801 (2023) - [i59]Karel D'Oosterlinck, François Remy, Johannes Deleu, Thomas Demeester, Chris Develder, Klim Zaporojets, Aneiss Ghodsi, Simon Ellershaw, Jack Collins, Christopher Potts:
BioDEX: Large-Scale Biomedical Adverse Drug Event Extraction for Real-World Pharmacovigilance. CoRR abs/2305.13395 (2023) - [i58]Maarten De Raedt, Fréderic Godin, Thomas Demeester, Chris Develder:
IDAS: Intent Discovery with Abstractive Summarization. CoRR abs/2305.19783 (2023) - [i57]François Remy, Thomas Demeester:
Automatic Glossary of Clinical Terminology: a Large-Scale Dictionary of Biomedical Definitions Generated from Ontological Knowledge. CoRR abs/2306.00665 (2023) - [i56]Semere Kiros Bitew, Johannes Deleu, A. Seza Dogruöz, Chris Develder, Thomas Demeester:
Learning from Partially Annotated Data: Example-aware Creation of Gap-filling Exercises for Language Learning. CoRR abs/2306.01584 (2023) - [i55]Jens-Joris Decorte, Severine Verlinden, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester:
Extreme Multi-Label Skill Extraction Training using Large Language Models. CoRR abs/2307.10778 (2023) - [i54]Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester:
Distractor generation for multiple-choice questions with predictive prompting and large language models. CoRR abs/2307.16338 (2023) - [i53]François Remy, Pieter Delobelle, Bettina Berendt, Kris Demuynck, Thomas Demeester:
Tik-to-Tok: Translating Language Models One Token at a Time: An Embedding Initialization Strategy for Efficient Language Adaptation. CoRR abs/2310.03477 (2023) - [i52]Karel D'Oosterlinck, Semere Kiros Bitew, Brandon Papineau, Christopher Potts, Thomas Demeester, Chris Develder:
CAW-coref: Conjunction-Aware Word-level Coreference Resolution. CoRR abs/2310.06165 (2023) - [i51]Sofie Labat, Thomas Demeester, Véronique Hoste:
EmoTwiCS: A Corpus for Modelling Emotion Trajectories in Dutch Customer Service Dialogues on Twitter. CoRR abs/2310.06536 (2023) - [i50]Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester:
Career Path Prediction using Resume Representation Learning and Skill-based Matching. CoRR abs/2310.15636 (2023) - [i49]Maarten De Raedt, Semere Kiros Bitew, Fréderic Godin, Thomas Demeester, Chris Develder:
Zero-Shot Cross-Lingual Sentiment Classification under Distribution Shift: an Exploratory Study. CoRR abs/2311.06549 (2023) - [i48]Karel D'Oosterlinck, Thomas Demeester, Chris Develder, Christopher Potts:
Flexible Model Interpretability through Natural Language Model Editing. CoRR abs/2311.10905 (2023) - [i47]Tom Van Der Meersch, Johannes Deleu, Thomas Demeester:
Training a Hopfield Variational Autoencoder with Equilibrium Propagation. CoRR abs/2311.15047 (2023) - [i46]Cédric Goemaere, Johannes Deleu, Thomas Demeester:
Accelerating Hierarchical Associative Memory: A Deep Equilibrium Approach. CoRR abs/2311.15673 (2023) - [i45]François Remy, Kris Demuynck, Thomas Demeester:
BioLORD-2023: Semantic Textual Representations Fusing LLM and Clinical Knowledge Graph Insights. CoRR abs/2311.16075 (2023) - [i44]Felix Koulischer, Cédric Goemaere, Tom Van Der Meersch, Johannes Deleu, Thomas Demeester:
Exploring the Temperature-Dependent Phase Transition in Modern Hopfield Networks. CoRR abs/2311.18434 (2023) - [i43]Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Stijn Vansteelandt, Thomas Demeester:
Synthetic Data: Can We Trust Statistical Estimators? CoRR abs/2312.07837 (2023) - 2022
- [c56]Klim Zaporojets, Johannes Deleu, Yiwei Jiang, Thomas Demeester, Chris Develder:
Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution. ACL (2) 2022: 778-784 - [c55]Yiwei Jiang, Amir Hadifar, Johannes Deleu, Thomas Demeester, Chris Develder:
UGent-T2K at the 2nd DialDoc Shared Task: A Retrieval-Focused Dialog System Grounded in Multiple Documents. DialDoc@ACL 2022: 115-122 - [c54]Sofie Labat, Amir Hadifar, Thomas Demeester, Véronique Hoste:
An Emotional Journey: Detecting Emotion Trajectories in Dutch Customer Service Dialogues. W-NUT@COLING 2022: 106-112 - [c53]François Remy, Kris Demuynck, Thomas Demeester:
BioLORD: Learning Ontological Representations from Definitions for Biomedical Concepts and their Textual Descriptions. EMNLP (Findings) 2022: 1454-1465 - [c52]Maarten De Raedt, Fréderic Godin, Chris Develder, Thomas Demeester:
Robustifying Sentiment Classification by Maximally Exploiting Few Counterfactuals. EMNLP 2022: 11386-11400 - [c51]Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester:
Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction. HR@RecSys 2022 - [c50]Ruben Janssens, Pieter Wolfert, Thomas Demeester, Tony Belpaeme:
"Cool glasses, where did you get them?": Generating Visually Grounded Conversation Starters for Human-Robot Dialogue. HRI 2022: 821-825 - [c49]Yoan Antonio López Rodríguez, Hector Raúl González Diez, Orlando Grabiel Toledano-López, Yusniel Hidalgo-Delgado, Erik Mannens, Thomas Demeester:
DLIME-Graphs: A DLIME Extension Based on Triple Embedding for Graphs. KGSWC 2022: 76-89 - [c48]Sofie Labat, Naomi Ackaert, Thomas Demeester, Véronique Hoste:
Variation in the Expression and Annotation of Emotions: A Wizard of Oz Pilot Study. NLPerspectives@LREC 2022: 66-72 - [c47]Klim Zaporojets, Lucie-Aimée Kaffee, Johannes Deleu, Thomas Demeester, Chris Develder, Isabelle Augenstein:
TempEL: Linking Dynamically Evolving and Newly Emerging Entities. NeurIPS 2022 - [c46]Orlando Grabiel Toledano-López, Julio Madera, Héctor R. Gonzalez, Alfredo Simón-Cuevas, Thomas Demeester, Erik Mannens:
Fine-tuning mT5-based Transformer via CMA-ES for Sentiment Analysis. IberLEF@SEPLN 2022 - [d1]Semere Kiros Bitew, Amir Hadifar, Lucas Sterckx, Johannes Deleu, Chris Develder, Thomas Demeester:
Distractor Retrieval Dataset. IEEE DataPort, 2022 - [i42]Yiwei Jiang, Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder:
CookDial: A dataset for task-oriented dialogs grounded in procedural documents. CoRR abs/2206.08723 (2022) - [i41]Henri Arno, Klaas Mulier, Joke Baeck, Thomas Demeester:
Next-Year Bankruptcy Prediction from Textual Data: Benchmark and Baselines. CoRR abs/2208.11334 (2022) - [i40]Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester:
Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction. CoRR abs/2209.05987 (2022) - [i39]Amir Hadifar, Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester:
EduQG: A Multi-format Multiple Choice Dataset for the Educational Domain. CoRR abs/2210.06104 (2022) - [i38]Maarten De Raedt, Fréderic Godin, Chris Develder, Thomas Demeester:
Robustifying Sentiment Classification by Maximally Exploiting Few Counterfactuals. CoRR abs/2210.11805 (2022) - [i37]François Remy, Kris Demuynck, Thomas Demeester:
BioLORD: Learning Ontological Representations from Definitions (for Biomedical Concepts and their Textual Descriptions). CoRR abs/2210.11892 (2022) - [i36]Semere Kiros Bitew, Amir Hadifar, Lucas Sterckx, Johannes Deleu, Chris Develder, Thomas Demeester:
Learning to Reuse Distractors to support Multiple Choice Question Generation in Education. CoRR abs/2210.13964 (2022) - [i35]Paloma Rabaey, Cedric De Boom, Thomas Demeester:
Neural Bayesian Network Understudy. CoRR abs/2211.08243 (2022) - 2021
- [j16]Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt:
Neural probabilistic logic programming in DeepProbLog. Artif. Intell. 298: 103504 (2021) - [j15]Gilles Vandewiele, Isabelle Dehaene, György Kovács, Lucas Sterckx, Olivier Janssens, Femke Ongenae, Femke De Backere, Filip De Turck, Kristien Roelens, Johan Decruyenaere, Sofie Van Hoecke, Thomas Demeester:
Overly optimistic prediction results on imbalanced data: a case study of flaws and benefits when applying over-sampling. Artif. Intell. Medicine 111: 101987 (2021) - [j14]Klim Zaporojets, Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Solving arithmetic word problems by scoring equations with recursive neural networks. Expert Syst. Appl. 174: 114704 (2021) - [j13]Klim Zaporojets, Johannes Deleu, Chris Develder, Thomas Demeester:
DWIE: An entity-centric dataset for multi-task document-level information extraction. Inf. Process. Manag. 58(4): 102563 (2021) - [j12]Amir Hadifar, Johannes Deleu, Chris Develder, Thomas Demeester:
Exploration of block-wise dynamic sparseness. Pattern Recognit. Lett. 151: 187-192 (2021) - [c45]Severine Verlinden, Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder:
Injecting Knowledge Base Information into End-to-End Joint Entity and Relation Extraction and Coreference Resolution. ACL/IJCNLP (Findings) 2021: 1952-1957 - [c44]Maarten De Raedt, Fréderic Godin, Pieter Buteneers, Chris Develder, Thomas Demeester:
A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders. EMNLP (1) 2021: 10108-10114 - [c43]Amir Hadifar, Sofie Labat, Véronique Hoste, Chris Develder, Thomas Demeester:
A Million Tweets Are Worth a Few Points: Tuning Transformers for Customer Service Tasks. NAACL-HLT 2021: 220-225 - [p1]Robin Manhaeve, Giuseppe Marra, Thomas Demeester, Sebastijan Dumancic, Angelika Kimmig, Luc De Raedt:
Neuro-Symbolic AI = Neural + Logical + Probabilistic AI. Neuro-Symbolic Artificial Intelligence 2021: 173-191 - [i34]Maarten De Raedt, Fréderic Godin, Pieter Buteneers, Chris Develder, Thomas Demeester:
A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders. CoRR abs/2104.03630 (2021) - [i33]Amir Hadifar, Sofie Labat, Véronique Hoste, Chris Develder, Thomas Demeester:
A Million Tweets Are Worth a Few Points: Tuning Transformers for Customer Service Tasks. CoRR abs/2104.07944 (2021) - [i32]Severine Verlinden, Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder:
Injecting Knowledge Base Information into End-to-End Joint Entity and Relation Extraction and Coreference Resolution. CoRR abs/2107.02286 (2021) - [i31]Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder:
Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution. CoRR abs/2108.13530 (2021) - [i30]Jens-Joris Decorte, Jeroen Van Hautte, Thomas Demeester, Chris Develder:
JobBERT: Understanding Job Titles through Skills. CoRR abs/2109.09605 (2021) - 2020
- [j11]Lucas Sterckx, Gilles Vandewiele, Isabelle Dehaene, Olivier Janssens, Femke Ongenae, Femke De Backere, Filip De Turck, Kristien Roelens, Johan Decruyenaere, Sofie Van Hoecke, Thomas Demeester:
Clinical information extraction for preterm birth risk prediction. J. Biomed. Informatics 110: 103544 (2020) - [c42]Thomas Demeester:
System Identification with Time-Aware Neural Sequence Models. AAAI 2020: 3757-3764 - [c41]Yiwei Jiang, Klim Zaporojets, Johannes Deleu, Thomas Demeester, Chris Develder:
Recipe Instruction Semantics Corpus (RISeC): Resolving Semantic Structure and Zero Anaphora in Recipes. AACL/IJCNLP 2020: 821-826 - [i29]Amir Hadifar, Johannes Deleu, Chris Develder, Thomas Demeester:
Block-wise Dynamic Sparseness. CoRR abs/2001.04686 (2020) - [i28]Gilles Vandewiele, Isabelle Dehaene, György Kovács, Lucas Sterckx, Olivier Janssens, Femke Ongenae, Femke De Backere, Filip De Turck, Kristien Roelens, Johan Decruyenaere, Sofie Van Hoecke, Thomas Demeester:
Overly Optimistic Prediction Results on Imbalanced Data: Flaws and Benefits of Applying Over-sampling. CoRR abs/2001.06296 (2020) - [i27]Klim Zaporojets, Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Solving Math Word Problems by Scoring Equations with Recursive Neural Networks. CoRR abs/2009.05639 (2020) - [i26]Klim Zaporojets, Johannes Deleu, Chris Develder, Thomas Demeester:
DWIE: an entity-centric dataset for multi-task document-level information extraction. CoRR abs/2009.12626 (2020)
2010 – 2019
- 2019
- [j10]Cedric De Boom, Thomas Demeester, Bart Dhoedt:
Character-level recurrent neural networks in practice: comparing training and sampling schemes. Neural Comput. Appl. 31(8): 4001-4017 (2019) - [c40]Gilles Vandewiele, Isabelle Dehaene, Olivier Janssens, Femke Ongenae, Femke De Backere, Filip De Turck, Kristien Roelens, Sofie Van Hoecke, Thomas Demeester:
Time-to-Birth Prediction Models and the Influence of Expert Opinions. AIME 2019: 286-291 - [c39]Gilles Vandewiele, Isabelle Dehaene, Olivier Janssens, Femke Ongenae, Femke De Backere, Filip De Turck, Kristien Roelens, Sofie Van Hoecke, Thomas Demeester:
A Critical Look at Studies Applying Over-Sampling on the TPEHGDB Dataset. AIME 2019: 355-364 - [c38]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Adversarial Perturbations for Joint Entity and Relation Extraction. BNAIC/BENELEARN 2019 - [c37]Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt:
DeepProbLog: Neural Probabilistic Logic Programming. BNAIC/BENELEARN 2019 - [c36]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Sub-event detection from twitter streams as a sequence labeling problem. NAACL-HLT (1) 2019: 745-750 - [c35]Luc De Raedt, Robin Manhaeve, Sebastijan Dumancic, Thomas Demeester, Angelika Kimmig:
Neuro-Symbolic = Neural + Logical + Probabilistic. NeSy@IJCAI 2019 - [c34]Amir Hadifar, Lucas Sterckx, Thomas Demeester, Chris Develder:
A Self-Training Approach for Short Text Clustering. RepL4NLP@ACL 2019: 194-199 - [i25]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Sub-event detection from Twitter streams as a sequence labeling problem. CoRR abs/1903.05396 (2019) - [i24]Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt:
DeepProbLog: Neural Probabilistic Logic Programming. CoRR abs/1907.08194 (2019) - [i23]Thomas Demeester:
System Identification with Time-Aware Neural Sequence Models. CoRR abs/1911.09431 (2019) - 2018
- [j9]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
An attentive neural architecture for joint segmentation and parsing and its application to real estate ads. Expert Syst. Appl. 102: 100-112 (2018) - [j8]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Joint entity recognition and relation extraction as a multi-head selection problem. Expert Syst. Appl. 114: 34-45 (2018) - [j7]Lucas Sterckx, Thomas Demeester, Johannes Deleu, Chris Develder:
Creation and evaluation of large keyphrase extraction collections with multiple opinions. Lang. Resour. Evaluation 52(2): 503-532 (2018) - [j6]Steven Van Canneyt, Philip Leroux, Bart Dhoedt, Thomas Demeester:
Modeling and predicting the popularity of online news based on temporal and content-related features. Multim. Tools Appl. 77(1): 1409-1436 (2018) - [j5]Cedric De Boom, Rohan Agrawal, Samantha Hansen, Esh Kumar, Romain Yon, Ching-Wei Chen, Thomas Demeester, Bart Dhoedt:
Large-scale user modeling with recurrent neural networks for music discovery on multiple time scales. Multim. Tools Appl. 77(12): 15385-15407 (2018) - [c33]Dirk Weissenborn, Pasquale Minervini, Isabelle Augenstein, Johannes Welbl, Tim Rocktäschel, Matko Bosnjak, Jeff Mitchell, Thomas Demeester, Tim Dettmers, Pontus Stenetorp, Sebastian Riedel:
Jack the Reader - A Machine Reading Framework. ACL (4) 2018: 25-30 - [c32]Klim Zaporojets, Lucas Sterckx, Johannes Deleu, Thomas Demeester, Chris Develder:
Predicting Psychological Health from Childhood Essays. The UGent-IDLab CLPsych 2018 Shared Task System. CLPsych@NAACL-HTL 2018: 119-125 - [c31]Thomas Demeester, Johannes Deleu, Fréderic Godin, Chris Develder:
Predefined Sparseness in Recurrent Sequence Models. CoNLL 2018: 324-333 - [c30]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Adversarial training for multi-context joint entity and relation extraction. EMNLP 2018: 2830-2836 - [c29]Fréderic Godin, Kris Demuynck, Joni Dambre, Wesley De Neve, Thomas Demeester:
Explaining Character-Aware Neural Networks for Word-Level Prediction: Do They Discover Linguistic Rules? EMNLP 2018: 3275-3284 - [c28]Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt:
DeepProbLog: Neural Probabilistic Logic Programming. NeurIPS 2018: 3753-3763 - [i22]Cedric De Boom, Thomas Demeester, Bart Dhoedt:
Character-level Recurrent Neural Networks in Practice: Comparing Training and Sampling Schemes. CoRR abs/1801.00632 (2018) - [i21]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Joint entity recognition and relation extraction as a multi-head selection problem. CoRR abs/1804.07847 (2018) - [i20]Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt:
DeepProbLog: Neural Probabilistic Logic Programming. CoRR abs/1805.10872 (2018) - [i19]Dirk Weissenborn, Pasquale Minervini, Tim Dettmers, Isabelle Augenstein, Johannes Welbl, Tim Rocktäschel, Matko Bosnjak, Jeff Mitchell, Thomas Demeester, Pontus Stenetorp, Sebastian Riedel:
Jack the Reader - A Machine Reading Framework. CoRR abs/1806.08727 (2018) - [i18]Lucas Sterckx, Johannes Deleu, Chris Develder, Thomas Demeester:
Prior Attention for Style-aware Sequence-to-Sequence Models. CoRR abs/1806.09439 (2018) - [i17]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Adversarial training for multi-context joint entity and relation extraction. CoRR abs/1808.06876 (2018) - [i16]Thomas Demeester, Johannes Deleu, Fréderic Godin, Chris Develder:
Predefined Sparseness in Recurrent Sequence Models. CoRR abs/1808.08720 (2018) - [i15]Fréderic Godin, Kris Demuynck, Joni Dambre, Wesley De Neve, Thomas Demeester:
Explaining Character-Aware Neural Networks for Word-Level Prediction: Do They Discover Linguistic Rules? CoRR abs/1808.09551 (2018) - 2017
- [c27]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Reconstructing the house from the ad: Structured prediction on real estate classifieds. EACL (2) 2017: 274-279 - [c26]Lucas Sterckx, Jason Naradowsky, Bill Byrne, Thomas Demeester, Chris Develder:
Break it Down for Me: A Study in Automated Lyric Annotation. EMNLP 2017: 2074-2080 - [c25]Pasquale Minervini, Thomas Demeester, Tim Rocktäschel, Sebastian Riedel:
Adversarial Sets for Regularising Neural Link Predictors. UAI 2017 - [i14]Pasquale Minervini, Thomas Demeester, Tim Rocktäschel, Sebastian Riedel:
Adversarial Sets for Regularising Neural Link Predictors. CoRR abs/1707.07596 (2017) - [i13]Lucas Sterckx, Jason Naradowsky, Bill Byrne, Thomas Demeester, Chris Develder:
Break it Down for Me: A Study in Automated Lyric Annotation. CoRR abs/1708.03492 (2017) - [i12]Cedric De Boom, Rohan Agrawal, Samantha Hansen, Esh Kumar, Romain Yon, Ching-Wei Chen, Thomas Demeester, Bart Dhoedt:
Large-Scale User Modeling with Recurrent Neural Networks for Music Discovery on Multiple Time Scales. CoRR abs/1708.06520 (2017) - [i11]Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
An attentive neural architecture for joint segmentation and parsing and its application to real estate ads. CoRR abs/1709.09590 (2017) - 2016
- [j4]Thomas Demeester, Robin Aly, Djoerd Hiemstra, Dong Nguyen, Chris Develder:
Predicting relevance based on assessor disagreement: analysis and practical applications for search evaluation. Inf. Retr. J. 19(3): 284-312 (2016) - [j3]Lucas Sterckx, Thomas Demeester, Johannes Deleu, Chris Develder:
Knowledge base population using semantic label propagation. Knowl. Based Syst. 108: 79-91 (2016) - [j2]Cedric De Boom, Steven Van Canneyt, Thomas Demeester, Bart Dhoedt:
Representation learning for very short texts using weighted word embedding aggregation. Pattern Recognit. Lett. 80: 150-156 (2016) - [c24]Thomas Demeester, Tim Rocktäschel, Sebastian Riedel:
Regularizing Relation Representations by First-order Implications. AKBC@NAACL-HLT 2016: 75-80 - [c23]Thomas Demeester, Tim Rocktäschel, Sebastian Riedel:
Lifted Rule Injection for Relation Embeddings. EMNLP 2016: 1389-1399 - [c22]Lucas Sterckx, Cornelia Caragea, Thomas Demeester, Chris Develder:
Supervised Keyphrase Extraction as Positive Unlabeled Learning. EMNLP 2016: 1924-1929 - [c21]Baptist Vandersmissen, Lucas Sterckx, Thomas Demeester, Azarakhsh Jalalvand, Wesley De Neve, Rik Van de Walle:
An Automated End-To-End Pipeline for Fine-Grained Video Annotation using Deep Neural Networks. ICMR 2016: 409-412 - [i10]Cedric De Boom, Sam Leroux, Steven Bohez, Pieter Simoens, Thomas Demeester, Bart Dhoedt:
Efficiency Evaluation of Character-level RNN Training Schedules. CoRR abs/1605.02486 (2016) - [i9]Thomas Demeester, Tim Rocktäschel, Sebastian Riedel:
Lifted Rule Injection for Relation Embeddings. CoRR abs/1606.08359 (2016) - [i8]Cedric De Boom, Steven Van Canneyt, Thomas Demeester, Bart Dhoedt:
Representation learning for very short texts using weighted word embedding aggregation. CoRR abs/1607.00570 (2016) - [i7]Dong Nguyen, Thomas Demeester, Dolf Trieschnigg, Djoerd Hiemstra:
Resource Selection for Federated Search on the Web. CoRR abs/1609.04556 (2016) - 2015
- [c20]Cedric De Boom, Steven Van Canneyt, Steven Bohez, Thomas Demeester, Bart Dhoedt:
Learning Semantic Similarity for Very Short Texts. ICDM Workshops 2015: 1229-1234 - [c19]Thomas Demeester, Dolf Trieschnigg, Dong Nguyen, Djoerd Hiemstra, Ke Zhou:
FedWeb Greatest Hits: Presenting the New Test Collection for Federated Web Search. WWW (Companion Volume) 2015: 27-28 - [c18]Lucas Sterckx, Thomas Demeester, Johannes Deleu, Chris Develder:
Topical Word Importance for Fast Keyphrase Extraction. WWW (Companion Volume) 2015: 121-122 - [c17]Lucas Sterckx, Thomas Demeester, Johannes Deleu, Chris Develder:
When Topic Models Disagree: Keyphrase Extraction with Multiple Topic Models. WWW (Companion Volume) 2015: 123-124 - [i6]Lucas Sterckx, Thomas Demeester, Johannes Deleu, Chris Develder:
Ghent University - IBCN Participation in the TAC KBP 2015 Cold Start Slot Filling task. TAC 2015 - [i5]Lucas Sterckx, Thomas Demeester, Johannes Deleu, Chris Develder:
Knowledge Base Population using Semantic Label Propagation. CoRR abs/1511.06219 (2015) - [i4]Thomas Demeester, Robin Aly, Djoerd Hiemstra, Dong Nguyen, Chris Develder:
Predicting Relevance based on Assessor Disagreement: Analysis and Practical Applications for Search Evaluation. CoRR abs/1511.07237 (2015) - [i3]Cedric De Boom, Steven Van Canneyt, Steven Bohez, Thomas Demeester, Bart Dhoedt:
Learning Semantic Similarity for Very Short Texts. CoRR abs/1512.00765 (2015) - 2014
- [j1]Robin Aly, Thomas Demeester, Stephen Robertson:
Probabilistic models in IR and their relationships. Inf. Retr. 17(2): 177-201 (2014) - [c16]Ke Zhou, Thomas Demeester, Dong Nguyen, Djoerd Hiemstra, Dolf Trieschnigg:
Aligning Vertical Collection Relevance with User Intent. CIKM 2014: 1915-1918 - [c15]Lucas Sterckx, Thomas Demeester, Johannes Deleu, Laurent Mertens, Chris Develder:
Assessing Quality of Unsupervised Topics in Song Lyrics. ECIR 2014: 547-552 - [c14]Laurent Mertens, Thomas Demeester, Johannes Deleu, Matthias Feys, Chris Develder:
Entity Linking: Test Collections Revisited. FIRE 2014: 134-137 - [c13]Matthias Feys, Thomas Demeester, Blaz Fortuna, Johannes Deleu, Chris Develder:
On the robustness of event detection evaluation: a case study. FIRE 2014: 138-141 - [c12]Thomas Demeester, Dolf Trieschnigg, Dong Nguyen, Djoerd Hiemstra, Ke Zhou:
Overview of the TREC 2014 Federated Web Search Track. TREC 2014 - [c11]Thomas Demeester, Robin Aly, Djoerd Hiemstra, Dong Nguyen, Dolf Trieschnigg, Chris Develder:
Exploiting user disagreement for web search evaluation: an experimental approach. WSDM 2014: 33-42 - [c10]Steven Van Canneyt, Matthias Feys, Steven Schockaert, Thomas Demeester, Chris Develder, Bart Dhoedt:
Detecting Newsworthy Topics in Twitter. SNOW-DC@WWW 2014: 25-32 - 2013
- [c9]Thomas Demeester, Dong Nguyen, Dolf Trieschnigg, Chris Develder, Djoerd Hiemstra:
What Snippets Say About Pages. DIR 2013: 34-35 - [c8]Thomas Demeester, Dong Nguyen, Dolf Trieschnigg, Chris Develder, Djoerd Hiemstra:
Snippet-Based Relevance Predictions for Federated Web Search. ECIR 2013: 697-700 - [c7]Robin Aly, Djoerd Hiemstra, Thomas Demeester:
Taily: shard selection using the tail of score distributions. SIGIR 2013: 673-682 - [c6]Robin Aly, Djoerd Hiemstra, Dolf Trieschnigg, Thomas Demeester:
Mirex and Taily at TREC 2013. TREC 2013 - [c5]Thomas Demeester, Dolf Trieschnigg, Dong Nguyen, Djoerd Hiemstra:
Overview of the TREC 2013 Federated Web Search Track. TREC 2013 - [i2]Laurent Mertens, Thomas Demeester, Johannes Deleu, Chris Develder:
UGent Participation in the TAC 2013 Entity-Linking Task. TAC 2013 - 2012
- [c4]Thomas Demeester, Dong Nguyen, Dolf Trieschnigg, Chris Develder, Djoerd Hiemstra:
What Snippets Say about Pages in Federated Web Search. AIRS 2012: 250-261 - [c3]Dong Nguyen, Thomas Demeester, Dolf Trieschnigg, Djoerd Hiemstra:
Federated search in the wild: the combined power of over a hundred search engines. CIKM 2012: 1874-1878 - [c2]Thong Hoang Van Duc, Thomas Demeester, Johannes Deleu, Piet Demeester, Chris Develder:
UGent Participation in the Microblog Track 2012. TREC 2012 - [i1]Laurent Mertens, Thomas Demeester, Johannes Deleu, Chris Develder, Piet Demeester:
UGent Participation in the TAC 2012 Entity-Linking Task. TAC 2012 - 2011
- [c1]Robin Aly, Thomas Demeester:
Towards a Better Understanding of the Relationship between Probabilistic Models in IR. ICTIR 2011: 164-175
Coauthor Index
[j23] [j19] [c69] [i71] [i64] [j18] [j17] [c64] [c62] [c61] [c60] [c57] [i61] [i59] [i56] [i55] [i54] [i50] [i47] [i46] [i44] [c56] [c55] [c51] [c47] [d1] [i42] [i40] [i39] [i36] [j14] [j13] [j12] [c45] [i32] [i31] [c41] [i29] [i27] [i26] [c38] [c36] [i25] [j9] [j8] [j7] [c32] [c31] [c30] [i21] [i18] [i17] [i16] [c27] [i11] [j3] [c18] [c17] [i6] [i5] [c15] [c14] [c13] [i2] [c2] [i1]
[i74] [j23] [j22] [j19] [c68] [i73] [i69] [i66] [i65] [j18] [j17] [c64] [c62] [c61] [c60] [c57] [i61] [i59] [i58] [i56] [i55] [i54] [i52] [i50] [i49] [i48] [c56] [c55] [c52] [c51] [c47] [d1] [i42] [i40] [i39] [i38] [i36] [j14] [j13] [j12] [c45] [c44] [c43] [i34] [i33] [i32] [i31] [i30] [c41] [i29] [i27] [i26] [c38] [c36] [c34] [i25] [j9] [j8] [j7] [c32] [c31] [c30] [i21] [i18] [i17] [i16] [c27] [c26] [i13] [i11] [j4] [j3] [c22] [c18] [c17] [i6] [i5] [i4] [c15] [c14] [c13] [c11] [c10] [c9] [c8] [i2] [c4] [c2] [i1]
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