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  1. Luc Steels. Norms and AI.. N. Osman and L. Steels (Eds.): VALE 2023, LNCS 14520, pages 1-7, 2024. PDF BibTeX

    @article{,
	author = "Steels, Luc",
	title = "{Norms and AI.}",
	journal = "N. Osman and L. Steels (Eds.): VALE 2023, LNCS 14520",
	pages = "1-7",
	year = 2024,
	pdf = "https://muhai.org/images/papers/VALE-steels-2024.pdf"
}

  1. Katrien Beuls and Paul Van Eecke. Humans Learn Language from Situated Communicative Interactions. What about Machines?. Computational Linguistics, pages 1-34, August 2024. URL, DOI BibTeX

    @article{10.1162/coli_a_00534,
	author = "Beuls, Katrien and Van Eecke, Paul",
	title = "{Humans Learn Language from Situated Communicative Interactions. What about Machines?}",
	journal = "Computational Linguistics",
	pages = "1-34",
	year = 2024,
	month = 08,
	abstract = "{Humans acquire their native languages by taking part in communicative interactions with their caregivers. These interactions are meaningful, intentional, and situated in their everyday environment. The situated and communicative nature of the interactions is essential to the language acquisition process, as language learners depend on clues provided by the communicative environment to make sense of the utterances they perceive. As such, the linguistic knowledge they build up is rooted in linguistic forms, their meaning, and their communicative function. When it comes to machines, the situated, communicative, and interactional aspects of language learning are often passed over. This applies in particular to today’s large language models (LLMs), where the input is predominantly text-based, and where the distribution of character groups or words serves as a basis for modeling the meaning of linguistic expressions. In this article, we argue that this design choice lies at the root of a number of important limitations, in particular regarding the data hungriness of the models, their limited ability to perform human-like logical and pragmatic reasoning, and their susceptibility to biases. At the same time, we make a case for an alternative approach that models how artificial agents can acquire linguistic structures by participating in situated communicative interactions. Through a selection of experiments, we show how the linguistic knowledge that is captured in the resulting models is of a fundamentally different nature than the knowledge captured by LLMs and argue that this change of perspective provides a promising path towards more human-like language processing in machines.}",
	issn = "0891-2017",
	doi = "10.1162/coli_a_00534",
	url = "https://doi.org/10.1162/coli\_a\_00534",
	eprint = "https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli\_a\_00534/2464080/coli\_a\_00534.pdf"
}

  1. Jonas Doumen, Katrien Beuls and Paul Van Eecke. Modelling constructivist language acquisition through syntactico-semantic pattern finding. Royal Society Open Science 11:231998, 2024. URL BibTeX

    @article{doumen2024modelling,
	title = "Modelling constructivist language acquisition through syntactico-semantic pattern finding",
	author = "Doumen, Jonas and Beuls, Katrien and {Van Eecke}, Paul",
	year = 2024,
	volume = 11,
	pages = 231998,
	journal = "Royal Society Open Science",
	url = "https://royalsocietypublishing.org/doi/10.1098/rsos.231998"
}

  1. Shiyao Zhang, Omar Faruk, Robert Porzel, Dennis Küster, Tanja Schultz and Hui Liu. Examining the Effects of Human-Likeness of Avatars on Emotion Perception and Emotion Elicitation. In 6th International Conference on Activity and Behavior Computing (ABC2024). 2024. URL BibTeX

    @conference{Zhang2024avatar,
	author = "Zhang, Shiyao and Faruk, Omar and Porzel, Robert and Küster, Dennis and Schultz, Tanja and Liu, Hui",
	title = "Examining the Effects of Human-Likeness of Avatars on Emotion Perception and Emotion Elicitation",
	booktitle = "6th International Conference on Activity and Behavior Computing (ABC2024)",
	year = 2024,
	organization = "IEEE",
	url = "https://www.csl.uni-bremen.de/cms/images/documents/publications/ZhangFarukPorzelKuesterSchultzLiu_ABC2024.pdf"
}

  1. Thomas Mildner Kamyar Javanmardi Robert Porzel Nima Zargham Vino Avanesi and Rainer Malaka. HASI: A Model for Human-Agent Speech Interaction. In In Proceedings of CUI '24: ACM Conversational User Interfaces. July 2024. URL BibTeX

    @inproceedings{Zargham24,
	author = "Nima Zargham, Vino Avanesi, Thomas Mildner, Kamyar Javanmardi, Robert Porzel and Rainer Malaka",
	booktitle = "In Proceedings of CUI '24: ACM Conversational User Interfaces",
	month = "July",
	publisher = "ACM",
	title = "HASI: A Model for Human-Agent Speech Interaction",
	year = 2024,
	url = "https://dl.acm.org/doi/pdf/10.1145/3640794.3665885"
}

  1. Inès Blin, Lise Stork, Laura Spillner and Carlo Santagiustina. OKG: A Knowledge Graph for Fine-grained Understanding of Social Media Discourse on Inequality. In Proceedings of the 12th Knowledge Capture Conference 2023. 2023, 166–174. URL, DOI BibTeX

    @inproceedings{10.1145/3587259.3627557,
	author = "Blin, In\`{e}s and Stork, Lise and Spillner, Laura and Santagiustina, Carlo",
	title = "OKG: A Knowledge Graph for Fine-grained Understanding of Social Media Discourse on Inequality",
	year = 2023,
	isbn = 9798400701412,
	publisher = "Association for Computing Machinery",
	address = "New York, NY, USA",
	url = "https://doi.org/10.1145/3587259.3627557",
	doi = "10.1145/3587259.3627557",
	abstract = "In recent years, social media platforms such as Twitter have allowed people to voice their opinions by engaging in online discussions. The availability of such discussions has garnered interest amongst researchers in analyzing the dynamics on critical topics, such as inequality. Most of the current strategies are, however, limited with respect to conveying the fine-grained opinions of users, focusing on tasks such as sentiment analysis or topic modeling that extract coarse categorizations. In this work, we address this challenge by integrating a Twitter corpus with the output of finer-grained semantic parsing for the analysis of social media discourse. To do so, we first introduce the OBservatory Integrated Ontology (OBIO) that integrates social media metadata with various types of linguistic knowledge. We then present the Observatory Knowledge Graph (OKG), a knowledge graph in terms of the ontology, populated with tweets on inequality. We lastly provide use cases showing how the knowledge graph can be used as the backbone of a social media observatory, to facilitate a deeper understanding of social media discourse.",
	booktitle = "Proceedings of the 12th Knowledge Capture Conference 2023",
	pages = "166–174",
	numpages = 9,
	keywords = "Ontology Engineering and Population, Social Media Discourse",
	location = ", Pensacola, FL, USA, ",
	series = "K-CAP '23"
}

  1. Jens Nevens, Robin de Haes, Rachel Ringe, Mihai Pomarlan, Robert Porzel, Katrien Beuls and Paul van Eecke. A Benchmark for Recipe Understanding in Artificial Agents. In Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti and Nianwen Xue (eds.). Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). 2024, 22–42. URL BibTeX

    @inproceedings{Nevens2024-jy,
	title = "A Benchmark for Recipe Understanding in Artificial Agents",
	booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation ({LREC-COLING} 2024)",
	author = "Nevens, Jens and de Haes, Robin and Ringe, Rachel and Pomarlan, Mihai and Porzel, Robert and Beuls, Katrien and van Eecke, Paul",
	editor = "Calzolari, Nicoletta and Kan, Min-Yen and Hoste, Veronique and Lenci, Alessandro and Sakti, Sakriani and Xue, Nianwen",
	abstract = "This paper introduces a novel benchmark that has been designed as a test bed for evaluating whether artificial agents are able to understand how to perform everyday activities, with a focus on the cooking domain. Understanding how to cook recipes is a highly challenging endeavour due to the underspecified and grounded nature of recipe texts, combined with the fact that recipe execution is a knowledge-intensive and precise activity. The benchmark comprises a corpus of recipes, a procedural semantic representation language of cooking actions, qualitative and quantitative kitchen simulators, and a standardised evaluation procedure. Concretely, the benchmark task consists in mapping a recipe formulated in natural language to a set of cooking actions that is precise enough to be executed in the simulated kitchen and yields the desired dish. To overcome the challenges inherent to recipe execution, this mapping process needs to incorporate reasoning over the recipe text, the state of the simulated kitchen environment, common-sense knowledge, knowledge of the cooking domain, and the action space of a virtual or robotic chef. This benchmark thereby addresses the growing interest in human-centric systems that combine natural language processing and situated reasoning to perform everyday activities.",
	url = {https://aclanthology.org/2024.lrec-main.3" publisher = "ELRA and ICCL},
	pages = "22--42",
	month = "",
	year = 2024,
	address = "Torino, Italia"
}

  1. Lise Stork and Richard Zijdeman. MIRA-KG: A knowledge graph of hypotheses and findings for social demography research. 2023. URL BibTeX

    @misc{Stork2023-mf,
	title = "{MIRA-KG}: A knowledge graph of hypotheses and findings for social demography research",
	author = "Stork, Lise and Zijdeman, Richard",
	abstract = "A shift in scientific publishing from paper-based to knowledge-based practices promotes reproducibility, machine actionability and knowledge discovery. This is important for disciplines like social science, as study indicators are often social constructs such as race or education; hypothesis tests are challenging to compare in demographic research due to their limited temporal and spatial coverage; and natural language in research papers is often imprecise and ambiguous. Therefore, we present the MIRA-KG, consisting of: (1) an ontology for capturing social demography research, which links hypotheses and findings to evidence, (2) annotations of papers on health inequality in terms of the ontology, gathered by (i) prompting a Large Language Model to annotate paper abstracts using the ontology, (ii) mapping concepts to terms from NCBO BioPortal ontologies and GeoNames, and (iii) refining the final graph by a set of SHACL constraints, developed according to data quality criteria. The utility of the resource lies in its use for formally representing social demography research hypotheses, discovering research biases, discovery of knowledge, and the derivation of novel questions.This dataset was generated using the code available on Github at https://w3id.org/mira/ at version v1.0. It uses the following ontology: https://w3id.org/mira/ontology/.",
	publisher = "Zenodo",
	url = "https://2024.eswc-conferences.org/wp-content/uploads/2024/04/146640533.pdf",
	year = 2023
}

  1. Liesbet De Vos, Jens Nevens, Paul Van Eecke and Katrien Beuls. Construction grammar and procedural semantics for human-interpretable grounded language processing. Linguist. Vanguard, 0. URL BibTeX

    @article{De_Vos2024-zc,
	title = "Construction grammar and procedural semantics for human-interpretable grounded language processing",
	author = "De Vos, Liesbet and Nevens, Jens and Van Eecke, Paul and Beuls, Katrien",
	url = "https://researchportal.unamur.be/en/publications/construction-grammar-and-procedural-semantics-for-human-interpret",
	abstract = "Abstract Grounded language processing is a crucial component in many artificial intelligence systems, as it allows agents to communicate about their physical surroundings. State-of-the-art approaches typically employ deep learning techniques that perform end-to-end mappings between natural language expressions and representations grounded in the environment. Although these techniques achieve high levels of accuracy, they are often criticized for their lack of interpretability and their reliance on large amounts of training data. As an alternative, we propose a fully interpretable, data-efficient architecture for grounded language processing. The architecture is based on two main components. The first component comprises an inventory of human-interpretable concepts learned through task-based communicative interactions. These concepts connect the sensorimotor experiences of an agent to meaningful symbols that can be used for reasoning operations. The second component is a computational construction grammar that maps between natural language expressions and procedural semantic representations. These representations are grounded through their integration with the learned concepts. We validate the architecture using a variation on the CLEVR benchmark, achieving an accuracy of 96 \%. Our experiments demonstrate that the integration of a computational construction grammar with an inventory of interpretable grounded concepts can effectively achieve human-interpretable grounded language processing in the CLEVR environment.",
	journal = "Linguist. Vanguard",
	publisher = "Walter de Gruyter GmbH",
	month = "",
	year = "",
	language = "en"
}

  1. Sofia Baroncini, Luc Steels and Remi van Trijp. Semantic data retrieval and integration for supporting artworks interpretation through integrative narrative networks(Short paper). In Antonis Bikakis, Roberta Ferrario, Stéphane Jean, Béatrice Markhoff, Alessandro Mosca and Marianna Nicolosi Asmundo (eds.). Proceedings of the International Workshop on Semantic Web and Ontology Design for Cultural Heritage 3540. 2023. URL BibTeX

    @inproceedings{baroncini_semantic_2023,
	address = "Athens, Greece",
	series = "{CEUR} {Workshop} {Proceedings}",
	title = "Semantic data retrieval and integration for supporting artworks interpretation through integrative narrative networks({Short} paper)",
	volume = 3540,
	url = "https://ceur-ws.org/Vol-3540/#short2",
	language = "en",
	urldate = "2023-11-05",
	booktitle = "Proceedings of the {International} {Workshop} on {Semantic} {Web} and {Ontology} {Design} for {Cultural} {Heritage}",
	publisher = "CEUR",
	author = "Baroncini, Sofia and Steels, Luc and Trijp, Remi van",
	editor = "Bikakis, Antonis and Ferrario, Roberta and Jean, Stéphane and Markhoff, Béatrice and Mosca, Alessandro and Asmundo, Marianna Nicolosi",
	month = "",
	year = 2023
}

  1. Daniel Beßler, Robert Porzel, Mihai Pomarlan and Michael Beetz. Foundational Models for Manipulation Activity Parsing. In Timothy Jung, Claudia M tom Dieck and Sandra Maria Correia Loureiro (eds.). Extended Reality and Metaverse. 2023, 115–121. BibTeX

    @inproceedings{besler_foundational_2023,
	address = "Cham",
	title = "Foundational {Models} for {Manipulation} {Activity} {Parsing}",
	isbn = "978-3-031-25390-4",
	booktitle = "Extended {Reality} and {Metaverse}",
	publisher = "Springer International Publishing",
	author = "Beßler, Daniel and Porzel, Robert and Pomarlan, Mihai and Beetz, Michael",
	editor = "Jung, Timothy and tom Dieck, M. Claudia and Correia Loureiro, Sandra Maria",
	year = 2023,
	pages = "115--121"
}

  1. Mona Abdel-Keream, Daniel Beßler, Ayden Janssen, Sascha Jongebloed, Robin Nolte, Mihai Pomarlan and Robert Porzel. An Ontological Model of User Preferences. BibTeX

    @inproceedings{abdel-keream_ontological_nodate,
	title = "An {Ontological} {Model} of {User} {Preferences}",
	author = "Abdel-Keream, Mona and Beßler, Daniel and Janssen, Ayden and Jongebloed, Sascha and Nolte, Robin and Pomarlan, Mihai and Porzel, Robert"
}

  1. Robin Nolte, Mihai Pomarlan, Daniel Beßler, Robert Porzel, Rainer Malaka and John Bateman. Towards an Ontology for Robot Introspection and Metacognition. BibTeX

    @inproceedings{nolte_towards_nodate,
	title = "Towards an {Ontology} for {Robot} {Introspection} and {Metacognition}",
	author = "Nolte, Robin and Pomarlan, Mihai and Beßler, Daniel and Porzel, Robert and Malaka, Rainer and Bateman, John"
}

  1. Laura Spillner, Nima Zargham, Mihai Pomarlan, Robert Porzel and Rainer Malaka. Finding Uncommon Ground: A Human-Centered Model for Extrospective Explanations. In Proceedings of the 2023 IJCAI workshop on Explainable Artificial Intelligence (XAI). 2023. URL BibTeX

    @inproceedings{spillner_finding_2023,
	title = "Finding {Uncommon} {Ground}: {A} {Human}-{Centered} {Model} for {Extrospective} {Explanations}",
	booktitle = "Proceedings of the 2023 {IJCAI} workshop on {Explainable} {Artificial} {Intelligence} ({XAI})",
	author = "Spillner, Laura and Zargham, Nima and Pomarlan, Mihai and Porzel, Robert and Malaka, Rainer",
	url = "https://drive.google.com/file/d/1V2kpRVaHtzBWHXjojWgAjT2xNJkfQYYY/view",
	year = 2023
}

  1. Laura Spillner, Robert Porzel, Robin Nolte and Rainer Malaka. Conceptual Shadows: Visualizing Concept-specific Dimensions of Meaning in Word Embeddings with Self Organizing Maps. In CEUR WORKSHOP PROCEEDINGS. 2023. PDF BibTeX

    @inproceedings{spillner_conceptual_2023,
	title = "Conceptual {Shadows}: {Visualizing} {Concept}-specific {Dimensions} of {Meaning} in {Word} {Embeddings} with {Self} {Organizing} {Maps}",
	booktitle = "{CEUR} {WORKSHOP} {PROCEEDINGS}",
	publisher = "CEUR-WS",
	author = "Spillner, Laura and Porzel, Robert and Nolte, Robin and Malaka, Rainer",
	pdf = "https://ceur-ws.org/Vol-3637/paper6.pdf",
	year = 2023
}

  1. Laura Spillner, Rachel Ringe, Robert Porzel and Rainer Malaka. "My, my, how can i resist you? " - examining user reactions to bogus explanations of ai. In Marianna Bergamaschi Ganapini, Andrea Loreggia, Nicholas Mattei, Francesca Rossi, Biplav Srivastava and Brent Venable (eds.). Proceedings of the Workshop on Ethics and Trust in Human-AI Collaboration: Socio-Technical Approaches (ETHAICS 2023) 3547. 2023. URL BibTeX

    @inproceedings{spillner_my_2023,
	address = "Macao, August",
	series = "{CEUR} {Workshop} {Proceedings}",
	title = {"{My}, my, how can i resist you? " - examining user reactions to bogus explanations of ai},
	volume = 3547,
	shorttitle = {"{My}, my, how can {I} resist you?},
	url = "https://ceur-ws.org/Vol-3547/#paper2",
	language = "en",
	urldate = "2023-11-13",
	booktitle = "Proceedings of the {Workshop} on {Ethics} and {Trust} in {Human}-{AI} {Collaboration}: {Socio}-{Technical} {Approaches} ({ETHAICS} 2023)",
	publisher = "CEUR",
	author = "Spillner, Laura and Ringe, Rachel and Porzel, Robert and Malaka, Rainer",
	editor = "Ganapini, Marianna Bergamaschi and Loreggia, Andrea and Mattei, Nicholas and Rossi, Francesca and Srivastava, Biplav and Venable, Brent",
	month = "",
	year = 2023
}

  1. Lara Verheyen, Jérôme Botoko Ekila, Jens Nevens, Paul Van Eecke and Katrien Beuls. Neuro-symbolic procedural semantics for reasoning-intensive visual dialogue tasks. In Frontiers in Artificial Intelligence and Applications. Frontiers in artificial intelligence and applications series, IOS Press, 2023. BibTeX

    @incollection{Verheyen2023-za,
	title = "Neuro-symbolic procedural semantics for reasoning-intensive visual dialogue tasks",
	booktitle = "Frontiers in Artificial Intelligence and Applications",
	author = "Verheyen, Lara and Ekila, J{\'e}r{\^o}me Botoko and Nevens, Jens and Van Eecke, Paul and Beuls, Katrien",
	abstract = "This paper introduces a novel approach to visual dialogue that is based on neuro-symbolic procedural semantics. The approach builds further on earlier work on procedural semantics for visual question answering and expands it on the one hand with neuro-symbolic reasoning operations, and on the other hand with mechanisms that handle the challenges that are inherent to dialogue, in particular the incremental nature of the information that is conveyed. Concretely, we introduce (i) the use of a conversation memory as a data structure that explicitly and incrementally represents the information that is expressed during the subsequent turns of a dialogue, and (ii) the design of a neuro-symbolic procedural semantic representation that is grounded in both visual input and the conversation memory. We validate the methodology using the reasoning-intensive MNIST Dialog and CLEVR-Dialog benchmark challenges and achieve a question-level accuracy of 99.8\% and 99.2\% respectively. The methodology presented in this paper responds to the growing interest in the field of artificial intelligence in solving tasks that involve both low-level perception and high-level reasoning using a combination of neural and symbolic techniques.",
	publisher = "IOS Press",
	series = "Frontiers in artificial intelligence and applications",
	month = "",
	year = 2023
}

  1. Paul Van Eecke, Lara Verheyen, Tom Willaert and Katrien Beuls. The Candide model: How narratives emerge where observations meet beliefs. In Proceedings of the The 5th Workshop on Narrative Understanding. 2023, 48–57. URL BibTeX

    @inproceedings{van-eecke-etal-2023-candide,
	title = "The Candide model: How narratives emerge where observations meet beliefs",
	author = "Van Eecke, Paul and Verheyen, Lara and Willaert, Tom and Beuls, Katrien",
	booktitle = "Proceedings of the The 5th Workshop on Narrative Understanding",
	month = "",
	year = 2023,
	address = "Toronto, Canada",
	publisher = "Association for Computational Linguistics",
	url = "https://aclanthology.org/2023.wnu-1.7",
	pages = "48--57",
	abstract = "This paper presents the Candide model as a computational architecture for modelling human-like, narrative-based language understanding. The model starts from the idea that narratives emerge through the process of interpreting novel linguistic observations, such as utterances, paragraphs and texts, with respect to previously acquired knowledge and beliefs. Narratives are personal, as they are rooted in past experiences, and constitute perspectives on the world that might motivate different interpretations of the same observations. Concretely, the Candide model operationalises this idea by dynamically modelling the belief systems and background knowledge of individual agents, updating these as new linguistic observations come in, and exposing them to a logic reasoning engine that reveals the possible sources of divergent interpretations. Apart from introducing the foundational ideas, we also present a proof-of-concept implementation that demonstrates the approach through a number of illustrative examples."
}

  1. Paul Van Eecke, Katrien Beuls, Jérôme Botoko Ekila and Roxana R\u adulescu. Language games meet multi-agent reinforcement learning: A case study for the naming game. J. Lang. Evol. 7(2):213–223, 2022. BibTeX

    @article{Van_Eecke2022-wj,
	title = "Language games meet multi-agent reinforcement learning: A case study for the naming game",
	author = "Van Eecke, Paul and Beuls, Katrien and Botoko Ekila, J{\'e}r{\^o}me and R{\u a}dulescu, Roxana",
	abstract = "Abstract Today, computational models of emergent communication in populations of autonomous agents are studied through two main methodological paradigms: multi-agent reinforcement learning (MARL) and the language game paradigm. While both paradigms share their main objectives and employ strikingly similar methods, the interaction between both communities has so far been surprisingly limited. This can to a large extent be ascribed to the use of different terminologies and experimental designs, which sometimes hinder the detection and interpretation of one another's results and progress. Through this paper, we aim to remedy this situation by (1) formulating the challenge of re-conceptualising the language game experimental paradigm in the framework of MARL, and by (2) providing both an alignment between their terminologies and an MARL−based reformulation of the canonical naming game experiment. Tackling this challenge will enable future language game experiments to benefit from the rapid and promising methodological advances in the MARL community, while it will enable future MARL experiments on learning emergent communication to benefit from the insights and results gained through language game experiments. We strongly believe that this cross-pollination has the potential to lead to major breakthroughs in the modelling of how human-like languages can emerge and evolve in multi-agent systems.",
	journal = "J. Lang. Evol.",
	publisher = "Oxford University Press (OUP)",
	volume = 7,
	number = 2,
	pages = "213--223",
	month = "",
	year = 2022,
	copyright = "https://creativecommons.org/licenses/by/4.0/",
	language = "en"
}

  1. Katrien Beuls and Paul Van Eecke. Fluid Construction Grammar: State of the Art and Future Outlook. In Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023). 2023, 41–50. URL BibTeX

    @inproceedings{beuls-van-eecke-2023-fluid,
	title = "Fluid Construction Grammar: State of the Art and Future Outlook",
	author = "Beuls, Katrien and Van Eecke, Paul",
	booktitle = "Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023)",
	month = "",
	year = 2023,
	address = "Washington, D.C.",
	publisher = "Association for Computational Linguistics",
	url = "https://aclanthology.org/2023.cxgsnlp-1.6",
	pages = "41--50",
	abstract = "Fluid Construction Grammar (FCG) is a computational framework that provides a formalism for representing construction grammars and a processing engine that supports construction-based language comprehension and production. FCG is conceived as a computational operationalisation of the basic tenets of construction grammar. It thereby aims to establish more solid foundations for constructionist theories of language, while expanding their application potential in the fields of artificial intelligence and natural language understanding. This paper aims to provide a brief introduction to the FCG research programme, reflecting on what has been achieved so far and identifying key challenges for the future."
}

  1. L Verheyen, J Botoko Ekila, J Nevens, P Van Eecke and K Beuls. Hybrid Procedural Semantics for Visual Dialogue: An Interactive Web Demonstration. In Poster session presented at Workshop on semantic techniques for narrative-based understanding - IJCAI-ECAI 2022. 2022. BibTeX

    @incollection{Verheyen2022-ll,
	title = "Hybrid Procedural Semantics for Visual Dialogue: An Interactive Web Demonstration",
	booktitle = "Poster session presented at Workshop on semantic techniques for narrative-based understanding - {IJCAI-ECAI} 2022",
	author = "Verheyen, L and Botoko Ekila, J and Nevens, J and Van Eecke, P and Beuls, K",
	year = 2022,
	address = "Vienna, Austria"
}

  1. Rachel Ringe and Robert Porzel. Towards a Task-based Metric for Measuring Trust in Autonomous Robots for Everyday Activities. In Proceedings of the CHI TRAIT Workshop on Trust and Reliance in AI-Assisted Tasks. 2023. URL BibTeX

    @inproceedings{ringe2023taskbased,
	title = "Towards a Task-based Metric for Measuring Trust in Autonomous Robots for Everyday Activities",
	author = "Ringe, Rachel and Porzel, Robert",
	booktitle = "Proceedings of the CHI TRAIT Workshop on Trust and Reliance in AI-Assisted Tasks",
	year = 2023,
	location = "Hamburg, Germany",
	url = "https://chi-trait.github.io/papers/2023/CHI_TRAIT_2023_Paper_39.pdf"
}

  1. Jonas Doumen, Katrien Beuls and Paul Van Eecke. Modelling Language Acquisition through Syntactico-Semantic Pattern Finding. In Findings of the Association for Computational Linguistics: EACL 2023. 2023, 1317–1327. URL BibTeX

    @inproceedings{doumen-etal-2023-modelling,
	title = "Modelling Language Acquisition through Syntactico-Semantic Pattern Finding",
	author = "Doumen, Jonas and Beuls, Katrien and Van Eecke, Paul",
	booktitle = "Findings of the Association for Computational Linguistics: EACL 2023",
	month = "",
	year = 2023,
	address = "Dubrovnik, Croatia",
	publisher = "Association for Computational Linguistics",
	url = "https://aclanthology.org/2023.findings-eacl.99",
	pages = "1317--1327",
	abstract = "Usage-based theories of language acquisition have extensively documented the processes by which children acquire language through communicative interaction. Notably, Tomasello (2003) distinguishes two main cognitive capacities that underlie human language acquisition: intention reading and pattern finding. Intention reading is the process by which children try to continuously reconstruct the intended meaning of their interlocutors. Pattern finding refers to the process that allows them to distil linguistic schemata from multiple communicative interactions. Even though the fields of cognitive science and psycholinguistics have studied these processes in depth, no faithful computational operationalisations of these mechanisms through which children learn language exist to date. The research on which we report in this paper aims to fill part of this void by introducing a computational operationalisation of syntactico-semantic pattern finding. Concretely, we present a methodology for learning grammars based on similarities and differences in the form and meaning of linguistic observations alone. Our methodology is able to learn compositional lexical and item-based constructions of variable extent and degree of abstraction, along with a network of emergent syntactic categories. We evaluate our methodology on the CLEVR benchmark dataset and show that the methodology allows for fast, incremental and effective learning. The constructions and categorial network that result from the learning process are fully transparent and bidirectional, facilitating both language comprehension and production. Theoretically, our model provides computational evidence for the learnability of usage-based constructionist theories of language acquisition. Practically, the techniques that we present facilitate the learning of computationally tractable, usage-based construction grammars, which are applicable for natural language understanding and production tasks."
}

  1. Paul Van Eecke, Jens Nevens and Katrien Beuls. Neural heuristics for scaling constructional language processing. Journal of Language Modelling 10(2):287–314, 2022. URL BibTeX

    @article{Van Eecke_Nevens_Beuls_2022,
	title = "Neural heuristics for scaling constructional language processing",
	volume = 10,
	url = "https://jlm.ipipan.waw.pl/index.php/JLM/article/view/318",
	abstractnote = "<p>Constructionist approaches to language make use of form-meaning pairings, called constructions, to capture all linguistic knowledge that is necessary for comprehending and producing natural language expressions. Language processing consists then in combining the constructions of a grammar in such a way that they solve a given language comprehension or production problem. Finding such an adequate sequence of constructions constitutes a search problem that is combinatorial in nature and becomes intractable as grammars increase in size. In this paper, we introduce a neural methodology for learning heuristics that substantially optimise the search processes involved in constructional language processing. We validate the methodology in a case study for the CLEVR benchmark dataset. We show that our novel methodology outperforms state-of-the-art techniques in terms of size of the search space and time of computation, most markedly in the production direction. The results reported on in this paper have the potential to overcome the major efficiency obstacle that hinders current efforts in learning large-scale construction grammars, thereby contributing to the development of scalable constructional language processing systems.</p>",
	number = 2,
	journal = "Journal of Language Modelling",
	author = "Van Eecke, Paul and Nevens, Jens and Beuls, Katrien",
	year = 2022,
	month = "Dec.",
	pages = "287–314"
}

  1. Mihai Pomarlan, Maria M Hedblom and Robert Porzel. Curiously exploring affordance spaces of a pouring task. Expert Systems, pages e13213, 2022. URL, DOI BibTeX

    @article{PHP22,
	author = "Pomarlan, Mihai and Hedblom, Maria M. and Porzel, Robert",
	title = "Curiously exploring affordance spaces of a pouring task",
	journal = "Expert Systems",
	pages = "e13213",
	year = 2022,
	keywords = "affordances, cognitive robotics, curiosity driven learning",
	doi = "https://doi.org/10.1111/exsy.13213",
	url = "https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.13213",
	eprint = "https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.13213"
}

  1. Laura Spillner John Bateman Thomas Mildner Robert Porzel Mihai Pomarlan and Carlo Santagiustina. Narrativizing Knowledge Graphs. In Joint Proceedings of the 3th International Workshop on Artificial Intelligence Technologies for Legal Documents (AI4LEGAL 2022) and the 1st International Workshop on Knowledge Graph Summarization (KGSum 2022) co-located with the 21st International Semantic Web Conference (ISWC 2022). Virtual Event, Hangzhou, China, October 23-24. 2022, 100–111. PDF BibTeX

    @inproceedings{porzeletal22kgsum,
	author = "Robert Porzel, Mihai Pomarlan, Laura Spillner, John Bateman, Thomas Mildner and Carlo Santagiustina",
	title = "Narrativizing Knowledge Graphs",
	booktitle = "Joint Proceedings of the 3th International Workshop on Artificial Intelligence Technologies for Legal Documents (AI4LEGAL 2022) and the 1st International Workshop on Knowledge Graph Summarization (KGSum 2022) co-located with the 21st International Semantic Web Conference (ISWC 2022). Virtual Event, Hangzhou, China, October 23-24",
	year = 2022,
	pdf = "http://ceur-ws.org/Vol-3257/paper11.pdf",
	pages = "100--111"
}

  1. Jens Nevens, Jonas Doumen, Paul Van Eecke and Katrien Beuls. Language Acquisition through Intention Reading and Pattern Finding. In Proceedings of the 29th International Conference on Computational Linguistics. 2022, 15–25. URL BibTeX

    @inproceedings{nevens-etal-2022-language,
	title = "Language Acquisition through Intention Reading and Pattern Finding",
	author = "Nevens, Jens and Doumen, Jonas and Van Eecke, Paul and Beuls, Katrien",
	booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
	month = "",
	year = 2022,
	address = "Gyeongju, Republic of Korea",
	publisher = "International Committee on Computational Linguistics",
	url = "https://aclanthology.org/2022.coling-1.2",
	pages = "15--25"
}

  1. Inès Blin. Building a French Revolution Narrative from Wikidata. In Proceedings of the IJCAI/ECAI Workshop on Semantic Techniques for Narrative-based Understanding. July 2022. PDF BibTeX

    @inproceedings{blin2022buildingfrnarrative,
	author = "Blin, In{\`e}s",
	booktitle = "Proceedings of the IJCAI/ECAI Workshop on Semantic Techniques for Narrative-based Understanding",
	year = 2022,
	month = 07,
	title = "Building a French Revolution Narrative from Wikidata",
	pdf = "https://muhai.org/images/papers/2022_ijcai_workshop_semantic_techniques_narrative_based_understanding_blin_ines.pdf"
}

  1. Inès Blin. Building Narrative Structures from Knowledge Graphs. In European Semantic Web Conference. 2022, 234–251. URL PDF BibTeX

    @inproceedings{blin2022building,
	title = "Building Narrative Structures from Knowledge Graphs",
	author = "Blin, In{\`e}s",
	booktitle = "European Semantic Web Conference",
	pages = "234--251",
	year = 2022,
	organization = "Springer",
	pdf = "https://muhai.org/images/papers/2022_eswc_phd_symposium_blin_ines.pdf",
	url = "https://link.springer.com/chapter/10.1007/978-3-031-11609-4_38"
}

  1. Luc Steels (ed.). Foundations for Meaning and Understanding in Human-centric AI. Venice International University, 2022. URL, DOI BibTeX

    @book{steels_luc_ed_2022_6666820,
	author = "Steels (ed.), Luc",
	title = "{Foundations for Meaning and Understanding in Human-centric AI}",
	publisher = "Venice International University",
	year = 2022,
	address = "Venice, Italy",
	month = "",
	note = "{This is the first volume in a series exploring how AI systems can construct rich models of problem situations for deliberative intelligence}",
	doi = "10.5281/zenodo.6666820",
	url = "https://doi.org/10.5281/zenodo.6666820"
}

  1. Mihai Pomarlan and Robert Porzel. Narrative Objects. In Proceedings of the IJCAI/ECAI Workshop on Semantic Techniques for Narrative-based Understanding. July 2022. PDF BibTeX

    @inproceedings{PomPor,
	author = "Mihai Pomarlan and Robert Porzel",
	booktitle = "Proceedings of the IJCAI/ECAI Workshop on Semantic Techniques for Narrative-based Understanding",
	year = 2022,
	month = 07,
	title = "Narrative Objects",
	pdf = "https://muhai.org/images/papers/Pomarlan_2022_Narrative_Objects.pdf"
}

  1. Thomas Mildner Robert Porzel Laura Spillner Carlo R. M. A. Santagiustina. Towards Conflictual Narrative Mechanics. In Proceedings of the IJCAI/ECAI Workshop on Semantic Techniques for Narrative-based Understanding. July 2022. PDF BibTeX

    @inproceedings{spillner2022towards,
	author = "Laura Spillner, Carlo R. M. A. Santagiustina, Thomas Mildner, Robert Porzel",
	booktitle = "Proceedings of the IJCAI/ECAI Workshop on Semantic Techniques for Narrative-based Understanding",
	year = 2022,
	month = 07,
	title = "Towards Conflictual Narrative Mechanics",
	pdf = "https://muhai.org/images/papers/Spillner_2022_Towards_Conflictual_Narrative_Mechanics.pdf"
}

  1. Remi van Trijp, Katrien Beuls and Paul Van Eecke. The FCG Editor: An innovative environment for engineering computational construction grammars. PLOS ONE 17(6):1-27, 2022. URL PDF, DOI BibTeX

    @article{vantrijp2022fcg,
	doi = "10.1371/journal.pone.0269708",
	author = "van Trijp, Remi AND Beuls, Katrien AND {Van Eecke}, Paul",
	journal = "PLOS ONE",
	publisher = "Public Library of Science",
	title = "The FCG Editor: An innovative environment for engineering computational construction grammars",
	year = 2022,
	volume = 17,
	pages = "1-27",
	number = 6,
	pdf = "https://muhai.org/images/papers/vantrijp2022fcg.pdf",
	url = "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0269708"
}

  1. Maria Hedblom Mihai Pomarlan Vanja Sophie Cangalovic Johannes Pfau John Bateman M A Sebastian Höffner Robert Porzel and Rainer Malaka. Deep Understanding of Everyday Activity Commands for Household Robots. Semantic Web Journal: Special Issue on Semantic Web for Industrial Engineering: Research and Applications, 2022. PDF BibTeX

    @article{hoeffner22,
	author = "Sebastian Höffner, Robert Porzel, Maria M. Hedblom, Mihai Pomarlan, Vanja Sophie Cangalovic, Johannes Pfau, John A. Bateman and Rainer Malaka",
	title = "Deep Understanding of Everyday Activity Commands for Household Robots",
	journal = "Semantic Web Journal: Special Issue on Semantic Web for Industrial Engineering: Research and Applications",
	year = 2022,
	pdf = "http://muhai.org/images/papers/Hoffner2022.pdf"
}

  1. Nikolaos Kondylidis, Jie Zou and Evangelos Kanoulas. Category Aware Explainable Conversational Recommendation. , 2021. URL PDF, DOI BibTeX

    @article{https://doi.org/10.48550/arxiv.2103.08733,
	author = "Kondylidis, Nikolaos and Zou, Jie and Kanoulas, Evangelos",
	title = "Category Aware Explainable Conversational Recommendation",
	doi = "10.48550/ARXIV.2103.08733",
	year = 2021,
	url = "https://arxiv.org/abs/2103.08733",
	pdf = "https://micros2021.github.io/pubs/Kondylidis_MICROS2021.pdf",
	publisher = "arXiv",
	copyright = "Creative Commons Attribution 4.0 International"
}

  1. Laura Spillner and Nina Wenig. Talk to Me on My Level – Linguistic Alignment for Chatbots. Association for Computing Machinery, 2021. URL PDF BibTeX

    @inbook{10.1145/3447526.3472050,
	author = "Spillner, Laura and Wenig, Nina",
	title = "Talk to Me on My Level – Linguistic Alignment for Chatbots",
	year = 2021,
	isbn = 9781450383288,
	publisher = "Association for Computing Machinery",
	address = "New York, NY, USA",
	url = "https://doi.org/10.1145/3447526.3472050",
	booktitle = "Proceedings of the 23rd International Conference on Mobile Human-Computer Interaction",
	articleno = 45,
	numpages = 12,
	pdf = "https://muhai.org/images/papers/Talk_to_me_on_my_level___linguistic_alignment_for_chatbots.pdf"
}

  1. Maria Hedblom M Mihai Pomarlan and Robert Porzel. Panta Rhei: Curiosity-Driven Exploration to Learn the Image-Schematic Affordances of Pouring Liquids. In Proceedings of the 29th Irish Conference on Artificial Intelligence and Cognitive Science. 2021. PDF BibTeX

    @inproceedings{Pomarlan21,
	author = "Mihai Pomarlan, Maria M. Hedblom and Robert Porzel",
	title = "Panta Rhei: Curiosity-Driven Exploration to Learn the Image-Schematic Affordances of Pouring Liquids",
	booktitle = "Proceedings of the 29th Irish Conference on Artificial Intelligence and Cognitive Science",
	year = 2021,
	address = "Dublin, Ireland",
	pdf = "http://muhai.org/images/papers/Tea_time___pouring_with_image_schemas_and_robo_simulation.pdf"
}

  1. Robert Porzel. On Formalizing Narratives. In Proceedings of the JOWO – Ontology Workshops. 2021. PDF BibTeX

    @inproceedings{Porzel2021,
	title = "On Formalizing Narratives",
	author = "Porzel, Robert",
	year = 2021,
	booktitle = "Proceedings of the JOWO -- Ontology Workshops",
	address = "Bolzano, Italy",
	pdf = "http://ceur-ws.org/Vol-2969/paper31-CAOS.pdf"
}

  1. Robert Porzel Rainer Malaka Michael Beetz Maria Hedblom Mihai Pomarlan. Dynamic Action Selection Using Image Schema-Based Reasoning for Robots. In Proceedings of the JOWO – Ontology Workshops. 2021. PDF BibTeX

    @inproceedings{Hedblom2021,
	title = "Dynamic Action Selection Using Image Schema-Based Reasoning for Robots",
	author = "Maria Hedblom, Mihai Pomarlan, Robert Porzel, Rainer Malaka, Michael Beetz",
	year = 2021,
	booktitle = "Proceedings of the JOWO -- Ontology Workshops",
	address = "Bolzano, Italy",
	pdf = "http://ceur-ws.org/Vol-2969/paper33-CAOS.pdf"
}

  1. Luc Steels. Personal dynamic memories are necessary to deal with meaning and understanding in human-centric AI. In Alessandro Saffiotti, Luciano Serafini and Paul Lukowicz (eds.). Proceedings of the First International Workshop on New Foundations for Human-Centered AI (NeHuAI) co-located with 24th European Conference on Artificial Intelligence (ECAI 2020), Santiago de Compostella, Spain, September 4, 2020 2659. 2020, 11–16. URL BibTeX

    @inproceedings{DBLP:conf/ecai/Steels20,
	author = "Luc Steels",
	editor = "Alessandro Saffiotti and Luciano Serafini and Paul Lukowicz",
	title = "Personal dynamic memories are necessary to deal with meaning and understanding in human-centric {AI}",
	booktitle = "Proceedings of the First International Workshop on New Foundations for Human-Centered {AI} (NeHuAI) co-located with 24th European Conference on Artificial Intelligence {(ECAI} 2020), Santiago de Compostella, Spain, September 4, 2020",
	series = "{CEUR} Workshop Proceedings",
	volume = 2659,
	pages = "11--16",
	publisher = "CEUR-WS.org",
	year = 2020,
	url = "http://ceur-ws.org/Vol-2659/steels.pdf",
	timestamp = "Wed, 30 Sep 2020 16:54:04 +0200",
	biburl = "https://dblp.org/rec/conf/ecai/Steels20.bib",
	bibsource = "dblp computer science bibliography, https://dblp.org} url = {https://muhai.org/images/papers/ecai-2020.pdf"
}

  1. Sinem Aslan and Luc Steels. Identifying Centres of Interest in Paintings Using Alignment and Edge Detection. In Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante and Roberto Vezzani (eds.). Pattern Recognition. ICPR International Workshops and Challenges. 2021, 589–603. URL BibTeX

    @inproceedings{10.1007/978-3-030-68796-0_42,
	author = "Aslan, Sinem and Steels, Luc",
	editor = "Del Bimbo, Alberto and Cucchiara, Rita and Sclaroff, Stan and Farinella, Giovanni Maria and Mei, Tao and Bertini, Marco and Escalante, Hugo Jair and Vezzani, Roberto",
	title = "Identifying Centres of Interest in Paintings Using Alignment and Edge Detection",
	booktitle = "Pattern Recognition. ICPR International Workshops and Challenges",
	year = 2021,
	publisher = "Springer International Publishing",
	address = "Cham",
	pages = "589--603",
	abstract = "What is the creative process through which an artist goes from an original image to a painting? Can we examine this process using techniques from computer vision and pattern recognition? Here we set the first preliminary steps to algorithmically deconstruct some of the transformations that an artist applies to an original image in order to establish centres of interest, which are focal areas of a painting that carry meaning. We introduce a comparative methodology that first cuts out the minimal segment from the original image on which the painting is based, then aligns the painting with this source, investigates micro-differences to identify centres of interest and attempts to understand their role. In this paper we focus exclusively on micro-differences with respect to edges. We believe that research into where and how artists create centres of interest in paintings is valuable for curators, art historians, viewers, and art educators, and might even help artists to understand and refine their own artistic method.",
	isbn = "978-3-030-68796-0",
	url = "https://link.springer.com/chapter/10.1007/978-3-030-68796-0_42"
}

  1. Vanja Sophie Cangalovic, Robert Porzel and John A Bateman. Streamlining Formal Construction Grammar. In Proceedings of the 11th International Conference on Construction Grammar. 2021. PDF BibTeX

    @inproceedings{key:inproceedings,
	author = "Cangalovic, Vanja Sophie and Porzel, Robert and Bateman, John A.",
	title = "Streamlining Formal Construction Grammar",
	booktitle = "Proceedings of the 11th International Conference on Construction Grammar",
	year = 2021,
	pdf = "https://muhai.org/images/papers/ICCG_workshop_2.pdf"
}

  1. Vanja Sophie Cangalovic Robert Porzel and John A Bateman. Filling Constructions: Applying Construction Grammar in the Kitchen. In Proceedings of the 11th International Conference on Construction Grammar. 2021. PDF BibTeX

    @inproceedings{key:inproceedings,
	author = "Robert Porzel, Vanja Sophie Cangalovic and John A. Bateman",
	title = "Filling Constructions: Applying Construction Grammar in the Kitchen",
	booktitle = "Proceedings of the 11th International Conference on Construction Grammar",
	year = 2021,
	pdf = "https://muhai.org/images/papers/Porzel-Cangalovic-ICCG2021.pdf"
}