Demo Data from VLDB 2026 / reviewers in the wild / expert
Lonneke van der Plas
dblp:94/106
· DBLP profile ↗
22ranked-venue papers
3as first author
6since 2021 · last 2026
0000-0002-2871-2574ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 19 · 3 first-author · 5 since 2021Applied, interdisciplinary, general and emerging computing · 3 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
4 papers |
Information extraction and text analysis · 51% Representation and self-supervised learning · 24% Knowledge representation and reasoning · 24% |
Topics — the 7 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning
analogical reasoning |
0.7 | 1 | 2023 | Can language models learn analogical reasoning? Investigating training objectives and comparisons to human performance · EMNLP 2023 |
Machine learning › Representation and self-supervised learning › word representation
word embedding |
0.7 | 1 | 2023 | Can language models learn analogical reasoning? Investigating training objectives and comparisons to human performance · EMNLP 2023 |
Natural language and speech › Information extraction and text analysis
misinformation detection |
0.3 | 1 | 2025 | HintsOfTruth: A Multimodal Checkworthiness Detection Dataset with Real and Synthetic Claims · ACL (1) 2025 |
Natural language and speech › Information extraction and text analysis
semantic role labeling |
0.1 | 1 | 2009 | Abstraction and Generalisation in Semantic Role Labels: PropBank, VerbNet or both? · ACL/IJCNLP 2009 |
Natural language and speech › Information extraction and text analysis
lexical semantics |
0.1 | 2 | 2009 | Finding Synonyms Using Automatic Word Alignment and Measures of Distributional Similarity · ACL 2006 Abstraction and Generalisation in Semantic Role Labels: PropBank, VerbNet or both? · ACL/IJCNLP 2009 |
Natural language and speech › Information extraction and text analysis › lexical resources › lexical resource construction
synonym discovery |
0.1 | 1 | 2006 | Finding Synonyms Using Automatic Word Alignment and Measures of Distributional Similarity · ACL 2006 |
Natural language and speech › Machine translation › statistical machine translation
word alignment |
0.0 | 1 | 2006 | Finding Synonyms Using Automatic Word Alignment and Measures of Distributional Similarity · ACL 2006 |
Methods — techniques the papers use, named apart from their topics
fine-tuning · 1.5prompting · 0.9large language model · 0.9distributional similarity · 0.1automatic word alignment · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | The MultiplEYE Text Corpus: Towards a Diverse and Ever-Expanding Multilingual Text Corpus
Ramune Kaspere, Anna Bondar, Sergiu Nisioi, Maja Stegenwallner-Schütz, Hanne B. Søndergaard Knudsen, Ana Matic Skoric, Eva Pavlinusic Vilus, Dorota Klimek-Jankowska, Chiara Tschirner, Not Battesta Soliva, Deborah N. Jakobi, Cui Ding, Dima Abu Romi, Cengiz Acartürk, Matilda Agdler, Anton Marius Alexandru, Mohd Faizan Ansari, Annalisa Arcidiacono, Elizabete Ausma Velta Barisa, Ana Bautista, Lisa Beinborn, Yevgeni Berzak, Nedeljka Bjelanovic, Anna Isabelle Bothmann, Jan Brasser, Caterina Cacioli, Anila Çepani, Ilze Ceple, Adelina Çerpja, Dalí Chirino, Jan Chromý, Alessandro Corona Mendozza, Iria de-Dios-Flores, Nazik Dinçtopal Deniz, Ana Dosen, Kristian Elersic, Inmaculada Fajardo, Zigmunds Freibergs, Angelina Ganebnaya, Jessica Gomes, Annjo Klungervik Greenall, Alba Haveriku, Anamaria Hodivoianu, Yu-Yin Hsu, Amanda Isaksen, Andreia Janeiro, Kristine M. Jensen de López, Aleksandar Jevremovic, Vojislav Jovanovic, Hanna Kedzierska, Nik Kharlamov, Sara Kosutar, Nelda Kote, Vanja Kovic, Izabela Krejtz, Thyra Krosness, Oleksandra Kuvshynova, Eilam Lavy, Ella Lion, Marta Lockiewicz, Kaidi Lõo, Paula Luegi, Mircea Mihai Marin, Clara Martin, Svitlana Matvieieva, Diane C. Mézière, Xavier Mínguez-López, Valeriia Modina, Jurgita Motiejuniene, Marie-Luise Müller, Tolgonai Nasipbek kyzy, Jamal Abdul Nasir, Johanne Sofie Krog Nedergård, Aysegül Özkan, Patrizia Paggio, Marijan Palmovic, Maria Christina Panagiotopoulou, Alberto Parola, Helena Pérez, Klaudia Petersen, Anja Podlesek, Eva Pospísilová, Marta Praulina, Mikulás Preininger, Loredana Punga, Diego Rossini, Spela Rot, Habib Sani Yahaya, Irina A. Sekerina, Anne Gabija Skadina, Jordi Solé i Casals, Lonneke van der Plas, Saara M. Varjopuro, Spyridoula Varlokosta, João Veríssimo, Oskari Juhapekka Virtanen, Nemanja Vracar, Mila Dimitrova-Vulchanova, Ahmad Mustapha Wali, Peizheng Wu, Nilgün Yücel, Stefan Frank, Nora Hollenstein, Lena A. Jäger, Somayeh Bakhtiari |
LREC | 94 |
| 2026 | Modelling Analogies and Analogical Reasoning: Connecting Cognitive Science Theory and NLP ResearchabstractAbstract Analogical reasoning is an essential aspect of human cognition. In this paper, we summarize key theories about the processes underlying analogical reasoning from the cognitive science literature and relate it to current research in natural language processing. While these processes can be easily linked to concepts in NLP, they are generally not viewed through a cognitive lens. Furthermore, we show how these notions are relevant for several major challenges in NLP research, not directly related to analogy solving. This may guide researchers to better optimize relational understanding in text, as opposed to relying heavily on entity-level similarity. Molly R. Petersen, Claire E. Stevenson, Lonneke van der Plas |
Trans. Assoc. Comput. Linguistics | 3 |
| 2025 | HintsOfTruth: A Multimodal Checkworthiness Detection Dataset with Real and Synthetic ClaimsabstractMisinformation can be countered with factchecking, but the process is costly and slow.Identifying checkworthy claims is the first step, where automation can help scale fact-checkers' efforts.However, detection methods struggle with content that is (1) multimodal, (2) from diverse domains, and (3) synthetic.We introduce HINTSOFTRUTH, a public dataset for multimodal checkworthiness detection with 27K real-world and synthetic image/claim pairs.The mix of real and synthetic data makes this dataset unique and ideal for benchmarking detection methods.We compare fine-tuned and prompted Large Language Models (LLMs).We find that well-configured lightweight textbased encoders perform comparably to multimodal models but the former only focus on identifying non-claim-like content.Multimodal LLMs can be more accurate but come at a significant computational cost, making them impractical for large-scale applications.When faced with synthetic data, multimodal models perform more robustly. Michiel van der Meer, Pavel Korshunov, Sébastien Marcel, Lonneke van der Plas |
ACL (1) | 4 |
| 2025 | Evaluating Creative Short Story Generation in Humans and Large Language Models
Mete Ismayilzada, Claire E. Stevenson, Lonneke van der Plas |
ICCC | 3 |
| 2025 | Evaluating Morphological Compositional Generalization in Large Language ModelsabstractMete Ismayilzada, Defne Circi, Jonne Sälevä, Hale Sirin, Abdullatif Köksal, Bhuwan Dhingra, Antoine Bosselut, Duygu Ataman, Lonneke Van Der Plas. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2025. Mete Ismayilzada, Defne Circi, Jonne Sälevä, Hale Sirin, Abdullatif Köksal, Bhuwan Dhingra, Antoine Bosselut, Duygu Ataman, Lonneke van der Plas |
NAACL (Long Papers) | 9 |
| 2023 | Can language models learn analogical reasoning? Investigating training objectives and comparisons to human performanceabstractWhile analogies are a common way to evaluate word embeddings in NLP, it is also of interest to investigate whether or not analogical reasoning is a task in itself that can be learned.In this paper, we test several ways to learn basic analogical reasoning, specifically focusing on analogies that are more typical of what is used to evaluate analogical reasoning in humans than those in commonly used NLP benchmarks.Our experiments find that models are able to learn analogical reasoning, even with a small amount of data.We additionally compare our models to a dataset with a human baseline, and find that after training, models approach human performance. Molly R. Petersen, Lonneke van der Plas |
EMNLP | 2 |
| 2020 | The societal and ethical relevance of computational creativity
Michele Loi, Eleonora Viganò, Lonneke van der Plas |
ICCC | 3 |
| 2020 | Automatic Removal of Identifying Information in Official EU Languages for Public Administrations: The MAPA ProjectabstractThe European MAPA (Multilingual Anonymisation for Public Administrations) project aims at developing an open-source solution for automatic de-identification of medical and legal documents. We introduce here the context, partners and aims of the project, and report on preliminary results. Lucie Gianola, Eriks Ajausks, Victoria Arranz, Chomicha Bendahman, Laurent Bié, Claudia Borg, Aleix Cerdà-i-Cucó, Khalid Choukri, Montse Cuadros, Ona de Gibert Bonet, Hans Degroote, Elena Edelman, Thierry Etchegoyhen, Ángela Franco Torres, Mercedes García Hernandez, Aitor García-Pablos, Albert Gatt, Cyril Grouin, Manuel Herranz, Alejandro Kohan, Thomas Lavergne, Maite Melero, Patrick Paroubek, Mickaël Rigault, Mike Rosner, Roberts Rozis, Lonneke van der Plas, Rinalds Viksna, Pierre Zweigenbaum |
JURIX | 27 |
| 2020 | Annotating for Hate Speech: The MaNeCo Corpus and Some Input from Critical Discourse AnalysisabstractThis paper presents a novel scheme for the annotation of hate speech in corpora of Web 2.0 commentary. The proposed scheme is motivated by the critical analysis of posts made in reaction to news reports on the Mediterranean migration crisis and LGBTIQ+ matters in Malta, which was conducted under the auspices of the EU-funded C.O.N.T.A.C.T. project. Based on the realisation that hate speech is not a clear-cut category to begin with, appears to belong to a continuum of discriminatory discourse and is often realised through the use of indirect linguistic means, it is argued that annotation schemes for its detection should refrain from directly including the label ‘hate speech,’ as different annotators might have different thresholds as to what constitutes hate speech and what not. In view of this, we propose a multi-layer annotation scheme, which is pilot-tested against a binary ±hate speech classification and appears to yield higher inter-annotator agreement. Motivating the postulation of our scheme, we then present the MaNeCo corpus on which it will eventually be used; a substantial corpus of on-line newspaper comments spanning 10 years. Stavros Assimakopoulos, Rebecca Vella Muskat, Lonneke van der Plas, Albert Gatt |
LREC | 3 |
| 2020 | MASRI-HEADSET: A Maltese Corpus for Speech RecognitionabstractMaltese, the national language of Malta, is spoken by approximately 500,000 people. Speech processing for Maltese is still in its early stages of development. In this paper, we present the first spoken Maltese corpus designed purposely for Automatic Speech Recognition (ASR). The MASRI-HEADSET corpus was developed by the MASRI project at the University of Malta. It consists of 8 hours of speech paired with text, recorded by using short text snippets in a laboratory environment. The speakers were recruited from different geographical locations all over the Maltese islands, and were roughly evenly distributed by gender. This paper also presents some initial results achieved in baseline experiments for Maltese ASR using Sphinx and Kaldi. The MASRI HEADSET Corpus is publicly available for research/academic purposes. Carlos Daniel Hernandez Mena, Albert Gatt, Andrea DeMarco, Claudia Borg, Lonneke van der Plas, Amanda Muscat, Ian Padovani |
LREC | 5 |
| 2018 | Face2Text: Collecting an Annotated Image Description Corpus for the Generation of Rich Face Descriptions
Albert Gatt, Marc Tanti, Adrian Muscat, Patrizia Paggio, Reuben A. Farrugia, Claudia Borg, Kenneth P. Camilleri, Mike Rosner, Lonneke van der Plas |
LREC | 9 |
| 2017 | Multiword Expression Processing: A SurveyabstractMultiword expressions (MWEs) are a class of linguistic forms spanning conventional word boundaries that are both idiosyncratic and pervasive across different languages. The structure of linguistic processing that depends on the clear distinction between words and phrases has to be re-thought to accommodate MWEs. The issue of MWE handling is crucial for NLP applications, where it raises a number of challenges. The emergence of solutions in the absence of guiding principles motivates this survey, whose aim is not only to provide a focused review of MWE processing, but also to clarify the nature of interactions between MWE processing and downstream applications. We propose a conceptual framework within which challenges and research contributions can be positioned. It offers a shared understanding of what is meant by “MWE processing,” distinguishing the subtasks of MWE discovery and identification. It also elucidates the interactions between MWE processing and two use cases: Parsing and machine translation. Many of the approaches in the literature can be differentiated according to how MWE processing is timed with respect to underlying use cases. We discuss how such orchestration choices affect the scope of MWE-aware systems. For each of the two MWE processing subtasks and for each of the two use cases, we conclude on open issues and research perspectives. Matthieu Constant, Gülsen Eryigit, Johanna Monti, Lonneke van der Plas, Carlos Ramisch, Mike Rosner, Amalia Todirascu |
Comput. Linguistics | 4 |
| 2016 | Towards Unsupervised and Language-independent Compound Splitting using Inflectional Morphological TransformationsabstractIn this paper, we address the task of languageindependent, knowledge-lean and unsupervised compound splitting, which is an essential component for many natural language processing tasks such as machine translation.Previous methods on statistical compound splitting either include language-specific knowledge (e.g., linking elements) or rely on parallel data, which results in limited applicability.We aim to overcome these limitations by learning compounding morphology from inflectional information derived from lemmatized monolingual corpora.In experiments for Germanic languages, we show that our approach significantly outperforms language-dependent stateof-the-art methods in finding the correct split point and that word inflection is a good approximation for compounding morphology. Patrick Ziering, Lonneke van der Plas |
HLT-NAACL | 2 |
| 2015 | Towards a Better Semantic Role Labeling of Complex PredicatesabstractWe propose a way to automatically improve the annotation of verbal complex predicates in PropBank which until now has been treating language mostly in a compositional manner.In order to minimize the manual re-annotation effort, we build on the recently introduced concept of aliasing complex predicates to existing PropBank rolesets which encompass the same meaning and argument structure.We suggest to find aliases automatically by applying a multilingual distributional model that uses the translations of simple and complex predicates as features.Furthermore, we set up an annotation effort to obtain a frequency balanced, realistic test set for this task.Our method reaches an accuracy of 44% on this test set and 72% for the more frequent test items in a lenient evaluation, which is not far from the upper bounds from human annotation. Glorianna Jagfeld, Lonneke van der Plas |
HLT-NAACL | 2 |
| 2014 | Global Methods for Cross-lingual Semantic Role and Predicate Labelling
Lonneke van der Plas, Marianna Apidianaki, Chenhua Chen |
COLING | 1 |
| 2014 | What good are 'Nominalkomposita' for 'noun compounds': Multilingual Extraction and Structure Analysis of Nominal Compositions using Linguistic Restrictors
Patrick Ziering, Lonneke van der Plas |
COLING | 2 |
| 2013 | Multilingual Lexicon Bootstrapping - Improving a Lexicon Induction System Using a Parallel Corpus
Patrick Ziering, Lonneke van der Plas, Hinrich Schütze |
IJCNLP | 2 |
| 2013 | Bootstrapping Semantic Lexicons for Technical Domains
Patrick Ziering, Lonneke van der Plas, Hinrich Schütze |
IJCNLP | 2 |
| 2009 | Abstraction and Generalisation in Semantic Role Labels: PropBank, VerbNet or both?
Paola Merlo, Lonneke van der Plas |
ACL/IJCNLP | 2 |
| 2009 | Predicting how it sounds: re-ranking dialogue prompts based on TTS quality for adaptive spoken dialogue systems
Cédric Boidin, Verena Rieser, Lonneke van der Plas, Oliver Lemon, Jonathan Chevelu |
INTERSPEECH | 3 |
| 2006 | Finding Synonyms Using Automatic Word Alignment and Measures of Distributional Similarity
Lonneke van der Plas, Jörg Tiedemann |
ACL | 1 |
| 2004 | Automatic Keyword Extraction from Spoken Text. A Comparison of Two Lexical Resources: EDR and WordNet
Lonneke van der Plas, Vincenzo Pallotta, Martin Rajman, Hatem Ghorbel |
LREC | 1 |