Publications

• https://www.sciencedirect.com/science/article/pii/B9780323955041015830
• https://doi.org/10.1016/B978-0-323-95504-1.01583-0

@incollection{TEICH2026,
title = {Information Theory in Translation and Interpreting Studies},
author = {Elke Teich and Heike Przybyl and Ekaterina Lapshinova-Koltunski},
url = {https://www.sciencedirect.com/science/article/pii/B9780323955041015830},
doi = {https://doi.org/10.1016/B978-0-323-95504-1.01583-0},
year = {2026},
date = {2026},
booktitle = {Reference Module in Social Sciences},
isbn = {978-0-443-15785-1},
publisher = {Elsevier},
abstract = {

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The uniform information density (UID) hypothesis postulates that linguistic units are distributed in a text in such a way that the variance around an average information density is minimized. The relationship between information density and information status (IS) is so far underexplored. In this ongoing work, we project IS annotations on the English section of the CIEP+ corpus (Verkerk Talamo 2024) to parallel sections in other languages. We then use the projected annotations to evaluate the relationship between IS and information content in a typologically diverse sample of languages. Our preliminary findings indicate that there is an effect of information status on information density, with the directionality of the effect depending on language and part of speech.

• 2026.sigtyp-main.3     (0.33MB)
• https://aclanthology.org/2026.sigtyp-main.3/
• https://doi.org/10.18653/v1/2026.sigtyp-main.3

@inproceedings{steuer-etal-2026-evaluating,
title = {Evaluating the Interplay of Information Status and Information Content in a Multilingual Parallel Corpus},
author = {Julius Steuer and Toshiki Nakai and Andrew Dyer and Luigi Talamo and Annemarie Verkerk},
editor = {Ekaterina Vylomova and Andrei Shcherbakov and Priya Rani},
url = {https://aclanthology.org/2026.sigtyp-main.3/},
doi = {https://doi.org/10.18653/v1/2026.sigtyp-main.3},
year = {2026},
date = {2026},
booktitle = {Proceedings of the 8th Workshop on Research in Computational Linguistic Typology and Multilingual NLP},
isbn = {979-8-89176-374-6},
pages = {18-25},
publisher = {Association for Computational Linguistics},
address = {Rabat, Morocco},
abstract = {The uniform information density (UID) hypothesis postulates that linguistic units are distributed in a text in such a way that the variance around an average information density is minimized. The relationship between information density and information status (IS) is so far underexplored. In this ongoing work, we project IS annotations on the English section of the CIEP+ corpus (Verkerk Talamo 2024) to parallel sections in other languages. We then use the projected annotations to evaluate the relationship between IS and information content in a typologically diverse sample of languages. Our preliminary findings indicate that there is an effect of information status on information density, with the directionality of the effect depending on language and part of speech.},
pubstate = {published},
type = {inproceedings}
}

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Event boundaries are known to have an impact on how discrete events are remembered; however, the neural mechanisms supporting memory for boundaries themselves remain poorly understood. This study investigated how both event boundaries and preceding information are processed and remembered while listening to naturalistically spoken narratives. We recorded participants’ neural responses (event-related potentials) while they listened to stories where a critical word signaled either a predictable (no-event boundary) or an unpredictable (event boundary) action. Critical words in the boundary condition were better remembered than those in the no-event boundary condition and elicited a larger N400 amplitude. Crucially, a subsequent memory effect was observed only in the boundary condition, with remembered critical words eliciting more negative N400s than forgotten ones, highlighting the role of increased demands in conceptual semantic processing in episodic memory encoding. Furthermore, a retrograde subsequent memory effect emerged also exclusively in the boundary condition, with more negative amplitudes to critical words when preceding information was later remembered, consistent with the notion that boundaries trigger rapid reinstatement of a recently experienced event. These findings provide compelling evidence that event boundaries act as “cognitive anchor points” that enhance the encoding of new information and also contribute to the strengthening of recently encoded events.

• s13415-026-01399-0     (1.69MB)
• https://doi.org/10.3758/s13415-026-01399-0
• https://doi.org/10.3758/s13415-026-01399-0

@article{Zogaj_etal_ERP_2026,
title = {How the brain segments experience: ERP evidence of event boundaries enhancing memory formation in narratives},
author = {Doruntinë Zogaj and Regine Bader and Axel Mecklinger},
url = {https://doi.org/10.3758/s13415-026-01399-0},
doi = {https://doi.org/10.3758/s13415-026-01399-0},
year = {2026},
date = {2026},
journal = {Cognitive, Affective, & Behavioral Neuroscience},
pages = {1-18},
abstract = {Event boundaries are known to have an impact on how discrete events are remembered; however, the neural mechanisms supporting memory for boundaries themselves remain poorly understood. This study investigated how both event boundaries and preceding information are processed and remembered while listening to naturalistically spoken narratives. We recorded participants’ neural responses (event-related potentials) while they listened to stories where a critical word signaled either a predictable (no-event boundary) or an unpredictable (event boundary) action. Critical words in the boundary condition were better remembered than those in the no-event boundary condition and elicited a larger N400 amplitude. Crucially, a subsequent memory effect was observed only in the boundary condition, with remembered critical words eliciting more negative N400s than forgotten ones, highlighting the role of increased demands in conceptual semantic processing in episodic memory encoding. Furthermore, a retrograde subsequent memory effect emerged also exclusively in the boundary condition, with more negative amplitudes to critical words when preceding information was later remembered, consistent with the notion that boundaries trigger rapid reinstatement of a recently experienced event. These findings provide compelling evidence that event boundaries act as “cognitive anchor points” that enhance the encoding of new information and also contribute to the strengthening of recently encoded events.},
pubstate = {published},
type = {article}
}

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In this paper, we analyse coreference annotation of the German language, focussing on the phenomenon of simplification, that is, the tendency to use words and constructions that are assumed to be easier perceived, understood, or produced. Simplification is one of the tools used by language users in order to optimise communication effectively. We are interested in how simplification is reflected in coreference in two different language products exposed to the phenomena of simplification: simultaneous interpreting and Easy German. For this, we automatically annotate simplified texts with coreference. We then evaluate the outputs of automatic annotation. In addition, we also look into quantitative distributions of some coreference features. Our findings show that although the language products under analysis diverge in terms of simplification driving factors, they share some specific coreference features. We also show that this specificity may cause annotation errors in simplified language, e.g. in non-nominal or split antecedents.

• 2025.crac-1.2     (0.37MB)
• https://aclanthology.org/2025.crac-1.2/
• https://doi.org/10.18653/v1/2025.crac-1.2

@inproceedings{jablotschkin-etal-2025-coreference,
title = {Coreference in simplified German: Linguistic features and challenges of automatic annotation},
author = {Sarah Jablotschkin and Ekaterina Lapshinova-Koltunski and Heike Zinsmeister},
editor = {Maciej Ogrodniczuk and Michal Novak and Massimo Poesio and Sameer Pradhan and Vincent Ng},
url = {https://aclanthology.org/2025.crac-1.2/},
doi = {https://doi.org/10.18653/v1/2025.crac-1.2},
year = {2025},
date = {2025},
booktitle = {Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference},
pages = {12-23},
publisher = {Association for Computational Linguistics},
address = {Suzhou, China},
abstract = {In this paper, we analyse coreference annotation of the German language, focussing on the phenomenon of simplification, that is, the tendency to use words and constructions that are assumed to be easier perceived, understood, or produced. Simplification is one of the tools used by language users in order to optimise communication effectively. We are interested in how simplification is reflected in coreference in two different language products exposed to the phenomena of simplification: simultaneous interpreting and Easy German. For this, we automatically annotate simplified texts with coreference. We then evaluate the outputs of automatic annotation. In addition, we also look into quantitative distributions of some coreference features. Our findings show that although the language products under analysis diverge in terms of simplification driving factors, they share some specific coreference features. We also show that this specificity may cause annotation errors in simplified language, e.g. in non-nominal or split antecedents.},
pubstate = {published},
type = {inproceedings}
}

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Dieser Beitrag beschreibt eine Korpusstudie zu den englischen Übersetzungen von naturwissenschaftlichen Texten, die in Zeitschriften der Royal Society of London seit dem 17. Jhd. veröffentlicht wurden. Als Datengrundlage dient das Royal Society Corpus (RSC), welches vor allem originalsprachliche englische Fachartikel, aber auch eine beachtliche Anzahl von übersetzten englischen Beiträgen aus Zeitschriften wie den Philosophical Transactions und den Proceedings der Royal Society beinhaltet. In einem ersten Schritt werden die übersetzten Fachartikel in den Daten identifiziert und in einem zusammenfassenden Überblick im Hinblick auf ihre genauen Entstehungszeiten, Themen, Ausgangssprachen und Übersetzer analysiert. Dabei stellt sich u. a. heraus, dass die meisten Übersetzungen im RSC aus dem 18. Jhd. stammen. Daher werden in einem nächsten Schritt speziell diese Texte in Bezug auf ausgewählte linguistische Merkmale untersucht, welche geeignet sind, um eine übersetzungswissenschaftliche Universalienhypothese, und zwar die ‚Normalisierungshypothese‘, in einem historischen Kontext zu überprüfen. Hierbei soll geklärt werden, ob die übersetzten Texte durch sprachlich weniger innovative Merkmale geprägt sind als nicht-übersetzte englische Vergleichstexte aus dem RSC. Insgesamt zeigen die Ergebnisse, dass Normalisierung und eine stärkere Nutzung von konventionelleren sprachlichen Strukturen keine auf die historischen Wissenschaftsübersetzungen zutreffende Übersetzungspraktiken waren. Anschließend wird ein Ausblick auf den Aufbau eines multilingualen Parallelkorpus mit den übersetzten Fachartikeln und ihren jeweiligen Ausgangstexten gegeben, um weitere Untersuchungen zu prototypischen Übersetzungseigenschaften zu ermöglichen, bei denen auch der Einfluss der Ausgangstexte berücksichtigt werden kann.

• Menzel     (0.5MB)
• https://chronotopos.eu/cts/article/view/130
• https://doi.org/10.70596/cts130

@article{Menzel_2025,
title = {Eine korpusbasierte diachrone Untersuchung zu {\"u}bersetzten Wissenschaftsartikeln aus den Zeitschriften der Royal Society of London},
author = {Katrin Menzel},
url = {https://chronotopos.eu/cts/article/view/130},
doi = {https://doi.org/10.70596/cts130},
year = {2025},
date = {2025},
journal = {chronotopos – A Journal of Translation History},
pages = {31--57},
volume = {6},
number = {2},
abstract = {Dieser Beitrag beschreibt eine Korpusstudie zu den englischen {\"U}bersetzungen von naturwissenschaftlichen Texten, die in Zeitschriften der Royal Society of London seit dem 17. Jhd. ver{\"o}ffentlicht wurden. Als Datengrundlage dient das Royal Society Corpus (RSC), welches vor allem originalsprachliche englische Fachartikel, aber auch eine beachtliche Anzahl von {\"u}bersetzten englischen Beitr{\"a}gen aus Zeitschriften wie den Philosophical Transactions und den Proceedings der Royal Society beinhaltet. In einem ersten Schritt werden die {\"u}bersetzten Fachartikel in den Daten identifiziert und in einem zusammenfassenden {\"U}berblick im Hinblick auf ihre genauen Entstehungszeiten, Themen, Ausgangssprachen und {\"U}bersetzer analysiert. Dabei stellt sich u. a. heraus, dass die meisten {\"U}bersetzungen im RSC aus dem 18. Jhd. stammen. Daher werden in einem n{\"a}chsten Schritt speziell diese Texte in Bezug auf ausgew{\"a}hlte linguistische Merkmale untersucht, welche geeignet sind, um eine {\"u}bersetzungswissenschaftliche Universalienhypothese, und zwar die ‚Normalisierungshypothese‘, in einem historischen Kontext zu {\"u}berpr{\"u}fen. Hierbei soll gekl{\"a}rt werden, ob die {\"u}bersetzten Texte durch sprachlich weniger innovative Merkmale gepr{\"a}gt sind als nicht-{\"u}bersetzte englische Vergleichstexte aus dem RSC. Insgesamt zeigen die Ergebnisse, dass Normalisierung und eine st{\"a}rkere Nutzung von konventionelleren sprachlichen Strukturen keine auf die historischen Wissenschafts{\"u}bersetzungen zutreffende {\"U}bersetzungspraktiken waren. Anschlie{\ss}end wird ein Ausblick auf den Aufbau eines multilingualen Parallelkorpus mit den {\"u}bersetzten Fachartikeln und ihren jeweiligen Ausgangstexten gegeben, um weitere Untersuchungen zu prototypischen {\"U}bersetzungseigenschaften zu erm{\"o}glichen, bei denen auch der Einfluss der Ausgangstexte ber{\"u}cksichtigt werden kann.},
pubstate = {published},
type = {article}
}

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Word predictability affects comprehension and speech perception, yet its role in intercomprehension – understanding foreign languages without prior learning – remains understudied. While surprisal and entropy, derived from language models (LMs), capture different aspects of predictability, this study aims to explore how these estimates explain intercomprehension success. We asked German and English native speakers to translate Dutch cognates from spoken utterances with varied predictability. We extracted the estimates from cascade Automatic Speech Recognition with LM and LM-only approaches. Results revealed that both approaches explained translation accuracy to a similar extent, but only LM-only estimates were significant. Also, German speakers seem to leverage contextual information as in native comprehension, while English speakers do not. These findings highlight that beyond LM-based estimates, typological proximity shapes intercomprehension in varied predictability contexts.

• xue_etal_itg2025     (0.6MB)
• https://doi.org/10.30420/456617005

@inproceedings{Xue/etal:2025b,
title = {The role of surprisal and entropy in spoken intercomprehension: An experiment on translation of cognates with varied predictability},
author = {Wei Xue and Julius Steuer and Dietrich Klakow and Bernd M{\"o}bius},
doi = {https://doi.org/10.30420/456617005},
year = {2025},
date = {2025},
booktitle = {ITG Conference on Speech Communication},
pages = {21-25},
address = {Berlin, Germany},
abstract = {Word predictability affects comprehension and speech perception, yet its role in intercomprehension – understanding foreign languages without prior learning – remains understudied. While surprisal and entropy, derived from language models (LMs), capture different aspects of predictability, this study aims to explore how these estimates explain intercomprehension success. We asked German and English native speakers to translate Dutch cognates from spoken utterances with varied predictability. We extracted the estimates from cascade Automatic Speech Recognition with LM and LM-only approaches. Results revealed that both approaches explained translation accuracy to a similar extent, but only LM-only estimates were significant. Also, German speakers seem to leverage contextual information as in native comprehension, while English speakers do not. These findings highlight that beyond LM-based estimates, typological proximity shapes intercomprehension in varied predictability contexts.},
pubstate = {published},
type = {inproceedings}
}

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This paper introduces AFRIDOC-MT, a document-level multi-parallel translation dataset covering English and five African languages: Amharic, Hausa, Swahili, Yorùbá, and Zulu. The dataset comprises 334 health and 271 information technology news documents, all human-translated from English to these languages. We conduct document-level translation benchmark experiments by evaluating the ability of neural machine translation (NMT) models and large language models (LLMs) to translate between English and these languages, at both the sentence and pseudo-document levels, the outputs being realigned to form complete documents for evaluation. Our results indicate that NLLB-200 achieves the best average performance among the standard NMT models, while GPT-4o outperforms general-purpose LLMs. Fine-tuning selected models leads to substantial performance gains, but models trained on sentences struggle to generalize effectively to longer documents. Furthermore, our analysis reveals that some LLMs exhibit issues such as under-generation, over-generation, repetition of words and phrases, and off-target translations, specifically for translation into African languages.

• 2025.emnlp-main.1413     (1.2MB)
• https://aclanthology.org/2025.emnlp-main.1413/
• https://doi.org/10.18653/v1/2025.emnlp-main.1413

@inproceedings{alabi-etal-2025-afridoc,
title = {AFRIDOC-MT: Document-level MT Corpus for African Languages},
author = {Jesujoba Alabi and Israel Abebe Azime and Miaoran Zhang and Cristina Espa{\~n}a-Bonet and Rachel Bawden and Dawei Zhu and David Adelani and Clement Oyeleke Odoje and Idris Akinade and Iffat Maab and Davis David and Shamsuddeen Hassan Muhammad and Neo Putini and David O. Ademuyiwa and Andrew Caines and Dietrich Klakow},
editor = {Christos Christodoulopoulos and Tanmoy Chakraborty and Carolyn Rose and Violet Peng},
url = {https://aclanthology.org/2025.emnlp-main.1413/},
doi = {https://doi.org/10.18653/v1/2025.emnlp-main.1413},
year = {2025},
date = {2025},
booktitle = {Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing},
isbn = {979-8-89176-332-6},
pages = {27770-27806},
publisher = {Association for Computational Linguistics},
address = {Suzhou, China},
abstract = {This paper introduces AFRIDOC-MT, a document-level multi-parallel translation dataset covering English and five African languages: Amharic, Hausa, Swahili, Yorùb{\'a}, and Zulu. The dataset comprises 334 health and 271 information technology news documents, all human-translated from English to these languages. We conduct document-level translation benchmark experiments by evaluating the ability of neural machine translation (NMT) models and large language models (LLMs) to translate between English and these languages, at both the sentence and pseudo-document levels, the outputs being realigned to form complete documents for evaluation. Our results indicate that NLLB-200 achieves the best average performance among the standard NMT models, while GPT-4o outperforms general-purpose LLMs. Fine-tuning selected models leads to substantial performance gains, but models trained on sentences struggle to generalize effectively to longer documents. Furthermore, our analysis reveals that some LLMs exhibit issues such as under-generation, over-generation, repetition of words and phrases, and off-target translations, specifically for translation into African languages.},
pubstate = {published},
type = {inproceedings}
}

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With over 2,000 languages and potentially millions of speakers, Africa represents one of the richest linguistic regions in the world. Yet, this diversity is scarcely reflected in state-of-the-art natural language processing (NLP) systems and large language models (LLMs), which predominantly support a narrow set of high-resource languages. This exclusion not only limits the reach and utility of modern NLP technologies but also risks widening the digital divide across linguistic communities. Nevertheless, NLP research on African languages is active and growing. In recent years, there has been a surge of interest in this area, driven by several factors{—}including the creation of multilingual language resources, the rise of community-led initiatives, and increased support through funding programs. In this survey, we analyze 884 research papers on NLP for African languages published over the past five years, offering a comprehensive overview of recent progress across core tasks. We identify key trends shaping the field and conclude by outlining promising directions to foster more inclusive and sustainable NLP research for African languages.

• 2025.emnlp-main.1414     (0.56MB)
• https://aclanthology.org/2025.emnlp-main.1414/
• https://doi.org/10.18653/v1/2025.emnlp-main.1414

@inproceedings{alabi-etal-2025-charting,
title = {Charting the landscape of african nlp: Mapping progress and shaping the road ahead},
author = {Jesujoba Alabi and Michael Hedderich and David Adelani and Dietrich Klakow},
editor = {Christos Christodoulopoulos and Tanmoy Chakraborty and Carolyn Rose and Violet Peng},
url = {https://aclanthology.org/2025.emnlp-main.1414/},
doi = {https://doi.org/10.18653/v1/2025.emnlp-main.1414},
year = {2025},
date = {2025},
booktitle = {Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing},
isbn = {979-8-89176-332-6},
pages = {27807-27841},
publisher = {Association for Computational Linguistics},
address = {Suzhou, China},
abstract = {With over 2,000 languages and potentially millions of speakers, Africa represents one of the richest linguistic regions in the world. Yet, this diversity is scarcely reflected in state-of-the-art natural language processing (NLP) systems and large language models (LLMs), which predominantly support a narrow set of high-resource languages. This exclusion not only limits the reach and utility of modern NLP technologies but also risks widening the digital divide across linguistic communities. Nevertheless, NLP research on African languages is active and growing. In recent years, there has been a surge of interest in this area, driven by several factors{---}including the creation of multilingual language resources, the rise of community-led initiatives, and increased support through funding programs. In this survey, we analyze 884 research papers on NLP for African languages published over the past five years, offering a comprehensive overview of recent progress across core tasks. We identify key trends shaping the field and conclude by outlining promising directions to foster more inclusive and sustainable NLP research for African languages.},
pubstate = {published},
type = {inproceedings}
}

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Human languages show astonishing variety, yet their diversity is constrained by recurring patterns. Linguists have long argued over the extent and causes of these grammatical ‘universals’. Using Grambank—a comprehensive database of grammatical features across the world’s languages—we tested 191 proposed universals with Bayesian analyses that account for both genealogical descent and geographical proximity. We find statistical support for about a third of the proposed linguistic universals. The majority of these concern word order and hierarchical universals: two types that have featured prominently in earlier work. Evolutionary analyses show that languages tend to change in ways that converge on these preferred patterns. This suggests that, despite the vast design space of possible grammars, languages do not evolve entirely at random. Shared cognitive and communicative pressures repeatedly push languages towards similar solutions.

• s41562-025-02325-z     (2.84MB)
• https://doi.org/10.1038/s41562-025-02325-z
• https://doi.org/10.1038/s41562-025-02325-z

@article{Verkerk-etal-2025-Bayesian,
title = {Enduring constraints on grammar revealed by Bayesian spatiophylogenetic analyses},
author = {Annemarie Verkerk and Olena Shcherbakova and Hannah J. Haynie and Hedvig Skirgård and Christoph Rzymski and Quentin D. Atkinson and Simon J. Greenhill and Russell D. Gray},
url = {https://doi.org/10.1038/s41562-025-02325-z},
doi = {https://doi.org/10.1038/s41562-025-02325-z},
year = {2025},
date = {2025},
journal = {Nature Human Behaviour},
abstract = {Human languages show astonishing variety, yet their diversity is constrained by recurring patterns. Linguists have long argued over the extent and causes of these grammatical ‘universals’. Using Grambank—a comprehensive database of grammatical features across the world’s languages—we tested 191 proposed universals with Bayesian analyses that account for both genealogical descent and geographical proximity. We find statistical support for about a third of the proposed linguistic universals. The majority of these concern word order and hierarchical universals: two types that have featured prominently in earlier work. Evolutionary analyses show that languages tend to change in ways that converge on these preferred patterns. This suggests that, despite the vast design space of possible grammars, languages do not evolve entirely at random. Shared cognitive and communicative pressures repeatedly push languages towards similar solutions.},
pubstate = {published},
type = {article}
}

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• Höltje.etal.Frontiers.2025     (5.71MB)
• https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2025.1645907
• https://doi.org/10.3389/fnhum.2025.1645907

@article{höltje-etal-unexpected-2025,
title = {Unexpected words that become your best memories: How sentential constraint and word expectedness affect memory retrieval},
author = {Gerrit H{\"o}ltje and Regine Bader and Julia Me{\ss}mer and Doruntinë Zogaj and Axel Mecklinger},
url = {https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2025.1645907},
doi = {https://doi.org/10.3389/fnhum.2025.1645907},
year = {2025},
date = {2025},
journal = {Frontiers in Human Neuroscience},
volume = {19 - 2025},
abstract = {

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Multilingual language models excel across languages, yet how they internally encode grammatical tense remains largely unclear. We investigate how decoder-only transformers represent, transfer, and control tense across eight typologically diverse languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. We construct a synthetic tense-annotated dataset and combine probing, causal analysis, feature disentanglement, and model steering to LLaMA-3.1 8B. We show that tense emerges as a distinct signal from early layers and transfers most strongly within the same language family. Causal tracing reveals that attention outputs around layer 16 consistently carry cross-lingually transferable tense information. Leveraging sparse autoencoders in this subspace, we isolate and steer English tense-related features, improving target-tense prediction accuracy by up to 11%% in a downstream cloze task.

• 2025.mrl-main.17     (3.63MB)
• https://aclanthology.org/2025.mrl-main.17/
• https://doi.org/10.18653/v1/2025.mrl-main.17

@inproceedings{tumurchuluun-etal-2025-tenseloc,
title = {TenseLoC: Tense Localization and Control in a Multilingual LLM},
author = {Ariun-Erdene Tumurchuluun and Yusser Al Ghussin and David Mare{\v{c}ek and Josef van Genabith and Koel Dutta Chowdhury},
editor = {David Ifeoluwa Adelani and Catherine Arnett and Duygu Ataman and Tyler A. Chang and Hila Gonen and Rahul Raja and Fabian Schmidt and David Stap and Jiayi Wang},
url = {https://aclanthology.org/2025.mrl-main.17/},
doi = {https://doi.org/10.18653/v1/2025.mrl-main.17},
year = {2025},
date = {2025},
booktitle = {Proceedings of the 5th Workshop on Multilingual Representation Learning (MRL 2025)},
isbn = {979-8-89176-345-6},
pages = {243-264},
publisher = {Association for Computational Linguistics},
address = {Suzhuo, China},
abstract = {Multilingual language models excel across languages, yet how they internally encode grammatical tense remains largely unclear. We investigate how decoder-only transformers represent, transfer, and control tense across eight typologically diverse languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. We construct a synthetic tense-annotated dataset and combine probing, causal analysis, feature disentanglement, and model steering to LLaMA-3.1 8B. We show that tense emerges as a distinct signal from early layers and transfers most strongly within the same language family. Causal tracing reveals that attention outputs around layer 16 consistently carry cross-lingually transferable tense information. Leveraging sparse autoencoders in this subspace, we isolate and steer English tense-related features, improving target-tense prediction accuracy by up to 11%% in a downstream cloze task.},
pubstate = {published},
type = {inproceedings}
}

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We present a set of studies on filler particles in interpreting in the language pair EnglishGerman, asking whether, and if so to what extent, surprisal can explain their occurrence. It is widely acknowledged that filler particles are associated with planning effort in monolingual production, but their occurrence in interpreting has not been fully investigated. Surprisal is a measure from information theory that estimates the information content (in bits) of a unit (e.g. a word) in the context of other linguistic units (e.g. n preceding words). Importantly, there is abundant evidence that surprisal is proportional to cognitive effort, measured independently in behavioural experiments, which provides a useful tool for explaining the link between linguistic choice and language cognition. Looking at the words preceding and following a filler particle in the target language output, we investigate surprisal as a predictor of filler particle occurrence, placing a special focus on function words vs. content words that follow filler particles. Overall, our analysis shows that surprisal of following words is a good predictor of filler particles in interpreting.

• Surprisal-explain-the-occurrence-of-filler-particles-in-simultaneous-interpreting     (1.08MB)
• https://zenodo.org/records/17242254

@article{pollklaesener_2025_surprisal,
title = {Surprisal explains the occurrence of filler particles in simultaneous interpreting},
author = {Christina Pollkl{\"a}sener and Maria Kunilovskaya and Elke Teich},
url = {https://zenodo.org/records/17242254},
year = {2025},
date = {2025},
journal = {SKASE Journal of Translation and Interpreting, Special issue: Empirical translation and interpreting studies},
pages = {55–78},
volume = {18},
number = {2},
abstract = {We present a set of studies on filler particles in interpreting in the language pair EnglishGerman, asking whether, and if so to what extent, surprisal can explain their occurrence. It is widely acknowledged that filler particles are associated with planning effort in monolingual production, but their occurrence in interpreting has not been fully investigated. Surprisal is a measure from information theory that estimates the information content (in bits) of a unit (e.g. a word) in the context of other linguistic units (e.g. n preceding words). Importantly, there is abundant evidence that surprisal is proportional to cognitive effort, measured independently in behavioural experiments, which provides a useful tool for explaining the link between linguistic choice and language cognition. Looking at the words preceding and following a filler particle in the target language output, we investigate surprisal as a predictor of filler particle occurrence, placing a special focus on function words vs. content words that follow filler particles. Overall, our analysis shows that surprisal of following words is a good predictor of filler particles in interpreting.},
pubstate = {published},
type = {article}
}

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This paper presents an analysis of the syntagmatic productivity (SynProd) of different classes of multiword expressions (MWEs) in English scientific writing over time (mid 17th to 20th c.). SynProd refers to the variability of the syntagmatic context in which a word or other kind of linguistic unit is used. To measure SynProd, we use entropy. The study reveals that, similar to single-token units of various parts of speech, MWEs exhibit an increasing trend in syntagmatic productivity over time, particularly after the mid-19th century. Furthermore, when compared to similar parts of speech (PoS), MWEs show a more pronounced increase in SynProd over time.

• 2025.mwe-1.1     (0.55MB)
• https://aclanthology.org/2025.mwe-1.1/
• https://doi.org/10.18653/v1/2025.mwe-1.1

@inproceedings{alves-etal-2025-syntagmatic,
title = {Syntagmatic Productivity of MWEs in Scientific English},
author = {Diego Alves and Stefan Fischer and Elke Teich},
editor = {Atul Kr. Ojha and Voula Giouli and Verginica Barbu Mititelu and Mathieu Constant and Gra{\v{z}ina Korvel and A. Seza Doğru{\"o}z and Alexandre Rademaker},
url = {https://aclanthology.org/2025.mwe-1.1/},
doi = {https://doi.org/10.18653/v1/2025.mwe-1.1},
year = {2025},
date = {2025},
booktitle = {Proceedings of the 21st Workshop on Multiword Expressions (MWE 2025)},
isbn = {979-8-89176-243-5},
pages = {1-6},
publisher = {Association for Computational Linguistics},
address = {Albuquerque, New Mexico, U.S.A.},
abstract = {This paper presents an analysis of the syntagmatic productivity (SynProd) of different classes of multiword expressions (MWEs) in English scientific writing over time (mid 17th to 20th c.). SynProd refers to the variability of the syntagmatic context in which a word or other kind of linguistic unit is used. To measure SynProd, we use entropy. The study reveals that, similar to single-token units of various parts of speech, MWEs exhibit an increasing trend in syntagmatic productivity over time, particularly after the mid-19th century. Furthermore, when compared to similar parts of speech (PoS), MWEs show a more pronounced increase in SynProd over time.},
pubstate = {published},
type = {inproceedings}
}

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We investigate the interplay of noun phrase (NP) complexity and modification type, namely the choice between pre- and postmodification, using a corpus-based approach. Our dataset is the Royal Society Corpus (RSC, Fischer et al. 2020), a diachronic corpus of English scientific writing. We find that the number of dependents, length of the head noun and distance to the head noun{‚}s own syntactic head (typically the main verb) affect the likelihood of pre- vs. postmodification: NPs with more dependents are more likely to be premodified, NPs with a longer head noun and a head noun closer to its own head are more likely to be postmodified. In addition, we find an effect of syntactic role and definiteness as well as time: The likelihood of premodification over postmodification increases with time and subject NPs as well as indefinite NPs are more likely to be premodified than NPs in other syntactic roles or definite NPs.

• 2025.quasy-1.10     (0.22MB)
• https://aclanthology.org/2025.quasy-1.10/

@inproceedings{landwehr-2025-interplay,
title = {The Interplay of Noun Phrase Complexity and Modification Type in Scientific Writing},
author = {Isabell Landwehr},
editor = {Xinying Chen and Yaqin Wang},
url = {https://aclanthology.org/2025.quasy-1.10/},
year = {2025},
date = {2025},
booktitle = {Proceedings of the Third Workshop on Quantitative Syntax (QUASY, SyntaxFest 2025)},
isbn = {979-8-89176-293-0},
pages = {72-82},
publisher = {Association for Computational Linguistics},
address = {Ljubljana, Slovenia},
abstract = {We investigate the interplay of noun phrase (NP) complexity and modification type, namely the choice between pre- and postmodification, using a corpus-based approach. Our dataset is the Royal Society Corpus (RSC, Fischer et al. 2020), a diachronic corpus of English scientific writing. We find that the number of dependents, length of the head noun and distance to the head noun{'}s own syntactic head (typically the main verb) affect the likelihood of pre- vs. postmodification: NPs with more dependents are more likely to be premodified, NPs with a longer head noun and a head noun closer to its own head are more likely to be postmodified. In addition, we find an effect of syntactic role and definiteness as well as time: The likelihood of premodification over postmodification increases with time and subject NPs as well as indefinite NPs are more likely to be premodified than NPs in other syntactic roles or definite NPs.},
pubstate = {published},
type = {inproceedings}
}

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We explore how different types of nominal compound complexity in scientific writing, in particular different types of compound structure, affect the reading times of experts and novices. We consider both in-domain and out-of-domain reading and use PoTeC (Jakobi et al. 2024), a corpus containing eye-tracking data of German native speakers reading passages from scientific textbooks. Our results suggest that some compound types are associated with longer reading times and that experts may not only have an advantage while reading in-domain texts, but also while reading out-of-domain.

• 2025.acl-srw.25     (0.17MB)
• https://aclanthology.org/2025.acl-srw.25/
• https://doi.org/10.18653/v1/2025.acl-srw.25

@inproceedings{landwehr-etal-2025-exploring,
title = {Exploring the Effect of Nominal Compound Structure in Scientific Texts on Reading Times of Experts and Novices},
author = {Isabell Landwehr and Marie-Pauline Krielke and Stefania Degaetano-Ortlieb andJin Zhao and Mingyang Wang and Zhu Liu},
url = {https://aclanthology.org/2025.acl-srw.25/},
doi = {https://doi.org/10.18653/v1/2025.acl-srw.25},
year = {2025},
date = {2025},
booktitle = {Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)},
isbn = {979-8-89176-254-1},
pages = {396-408},
publisher = {Association for Computational Linguistics},
address = {Vienna, Austria},
abstract = {We explore how different types of nominal compound complexity in scientific writing, in particular different types of compound structure, affect the reading times of experts and novices. We consider both in-domain and out-of-domain reading and use PoTeC (Jakobi et al. 2024), a corpus containing eye-tracking data of German native speakers reading passages from scientific textbooks. Our results suggest that some compound types are associated with longer reading times and that experts may not only have an advantage while reading in-domain texts, but also while reading out-of-domain.},
pubstate = {published},
type = {inproceedings}
}

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This study investigates the occurrence of sentence-initial filler particles (e.g. euh, hum) in simultaneously interpreted and original speeches using a bidirectional English-German corpus of European Parliament debates. We assume that sentence-initial filler particles indicate planning difficulties at the conceptual level, whereas sentence-medial filler particles mark hesitations over syntactic structure or lexical access. Since interpreters convey the source speech and do not plan their own message, we expect differences between interpreting and original speeches. We operationalise conceptual complexity as average word surprisal per sentence and local lexical or syntactic production problems as surprisal of the word following the filler particle. Our findings indicate that sentence-initial filler particles appear in sentences with higher conceptual complexity but are not well associated with local retrieval difficulty.

• pollklasener25_diss     (1.25MB)
• https://www.isca-archive.org/tmp/diss_2025/pollklasener25_diss.pdf
• https://doi.org/10.21437/DiSS.2025-19

@inproceedings{pollklasener25_diss,
title = {Euh... where do interpreters hesitate? An information-theoretic perspective on sentence-initial filler particles in simultaneous interpreting},
author = {Christina Pollkl{\"a}sener and Maria Kunilovskaya},
url = {https://www.isca-archive.org/tmp/diss_2025/pollklasener25_diss.pdf},
doi = {https://doi.org/10.21437/DiSS.2025-19},
year = {2025},
date = {2025},
booktitle = {12th edition of the Disfluency in Spontaneous Speech Workshop (DiSS 2025)},
pages = {92-96},
abstract = {This study investigates the occurrence of sentence-initial filler particles (e.g. euh, hum) in simultaneously interpreted and original speeches using a bidirectional English-German corpus of European Parliament debates. We assume that sentence-initial filler particles indicate planning difficulties at the conceptual level, whereas sentence-medial filler particles mark hesitations over syntactic structure or lexical access. Since interpreters convey the source speech and do not plan their own message, we expect differences between interpreting and original speeches. We operationalise conceptual complexity as average word surprisal per sentence and local lexical or syntactic production problems as surprisal of the word following the filler particle. Our findings indicate that sentence-initial filler particles appear in sentences with higher conceptual complexity but are not well associated with local retrieval difficulty.},
pubstate = {published},
type = {inproceedings}
}

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Expectations about upcoming words play a central role in language comprehension, with expected words being processed more easily than less expected ones. Surprisal theory formalizes this relationship by positing that cognitive effort is proportional to a word’s negative log-probability in context, as determined by distributional, linguistic, and world knowledge constraints. The emergence of large language models (LLMs) demonstrating the capacity to compute richly contextualized surprisal estimates, has motivated their consideration as models of comprehension. We assess here the relationship of LLM surprisal with two key neural correlates of comprehension — the N400 and the P600 — which differ in sensitivity to semantic association and contextual expectancy. While prior work has focused on the N400, we propose that the P600 may offer a better index of surprisal, as it is unaffected by association while still patterning continuously with expectancy. Using regression-based ERPs (rERPs), we examine data from three German factorial studies to evaluate the extent to which LLM surprisal can account for ERP differences. Our results show that LLM surprisal captures neither component consistently. We find that it is contaminated by simple association, particularly in smaller LLMs. As a result, LLM surprisal can partially account for association-driven N400 effects, but not for the full attenuation of N400 effects. Correspondingly, this property of LLMs compromises their ability to model the P600, which is sensitive to expectancy but not to association.

• Krieger2024LimitsLLM     (1.21MB)
• https://www.sciencedirect.com/science/article/pii/S0006899325004020
• https://doi.org/10.1016/j.brainres.2025.149841

@article{KRIEGER2025149841,
title = {On the Limits of LLM Surprisal as a Functional Explanation of the N400 and P600},
author = {Benedict Krieger and Harm Brouwer and Christoph Aurnhammer and Matthew W. Crocker},
url = {https://www.sciencedirect.com/science/article/pii/S0006899325004020},
doi = {https://doi.org/10.1016/j.brainres.2025.149841},
year = {2025},
date = {2025},
journal = {Brain Research},
pages = {149841},
volume = {1865},
abstract = {Expectations about upcoming words play a central role in language comprehension, with expected words being processed more easily than less expected ones. Surprisal theory formalizes this relationship by positing that cognitive effort is proportional to a word's negative log-probability in context, as determined by distributional, linguistic, and world knowledge constraints. The emergence of large language models (LLMs) demonstrating the capacity to compute richly contextualized surprisal estimates, has motivated their consideration as models of comprehension. We assess here the relationship of LLM surprisal with two key neural correlates of comprehension -- the N400 and the P600 -- which differ in sensitivity to semantic association and contextual expectancy. While prior work has focused on the N400, we propose that the P600 may offer a better index of surprisal, as it is unaffected by association while still patterning continuously with expectancy. Using regression-based ERPs (rERPs), we examine data from three German factorial studies to evaluate the extent to which LLM surprisal can account for ERP differences. Our results show that LLM surprisal captures neither component consistently. We find that it is contaminated by simple association, particularly in smaller LLMs. As a result, LLM surprisal can partially account for association-driven N400 effects, but not for the full attenuation of N400 effects. Correspondingly, this property of LLMs compromises their ability to model the P600, which is sensitive to expectancy but not to association.},
pubstate = {published},
type = {article}
}

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Die Studie untersucht die Beziehung zwischen Informationsdichte und linguistischer Kodierung in der Phonetik sowie der menschlichen Sprachverarbeitung. Die Informationsdichte einer linguistischen Einheit wird in Bezug auf Surprisal (den negativen Logarithmus der Wahrscheinlichkeit einer Einheit in einem gegebenen Kontext) definiert. Die Effekte von Surprisal auf die phonetische Kodierung wurden hinsichtlich verschiedener Aspekte wie Formantenverläufe von Vokalen, Stimmhaftigkeit von Plosiven, Silbendauer und Vokaldispersion (auch im L2) untersucht, wobei Kontrollfaktoren der prosodischen Struktur sowie mögliche Interaktionen mit dem Lombard-Effekt und der prosodischen Struktur berücksichtigt wurden. Die Ergebnisse deuten darauf hin, dass Sprecher phonetische Details anpassen, um ein Gleichgewicht zwischen Informationsdichte und phonetischer Kodierung aufrechtzuerhalten.

• 14.-Andreeva-Spisanie___Wege-und-Umwege-zum-Wandel___VOL-1_Final-dragged     (0.73MB)
• https://journalgermscand.fcml.uni-sofia.bg/wp-content/uploads/2025/04/14.-Andreeva-Spisanie___Wege-und-Umwege-zum-Wandel___VOL-1_Final-dragged.pdf

@article{andreeva_2025_informationsdichte,
title = {Informationsdichte und die Vorhersagbarkeit der phonetischen Struktur},
author = {Bistra Andreeva and Ivan Yuen and Bernd M{\"o}bius and Omnia Ibrahim},
editor = {Mikaela Petkova-Kessanlis and Radka Ivanova and Reneta Kileva-Stamenova and Svetlana Arnaudova and Maria Endreva},
url = {https://journalgermscand.fcml.uni-sofia.bg/wp-content/uploads/2025/04/14.-Andreeva-Spisanie___Wege-und-Umwege-zum-Wandel___VOL-1_Final-dragged.pdf},
year = {2025},
date = {2025},
journal = {Journal for German and Scandinavian Studies},
volume = {1},
abstract = {Die Studie untersucht die Beziehung zwischen Informationsdichte und linguistischer Kodierung in der Phonetik sowie der menschlichen Sprachverarbeitung. Die Informationsdichte einer linguistischen Einheit wird in Bezug auf Surprisal (den negativen Logarithmus der Wahrscheinlichkeit einer Einheit in einem gegebenen Kontext) definiert. Die Effekte von Surprisal auf die phonetische Kodierung wurden hinsichtlich verschiedener Aspekte wie Formantenverl{\"a}ufe von Vokalen, Stimmhaftigkeit von Plosiven, Silbendauer und Vokaldispersion (auch im L2) untersucht, wobei Kontrollfaktoren der prosodischen Struktur sowie m{\"o}gliche Interaktionen mit dem Lombard-Effekt und der prosodischen Struktur ber{\"u}cksichtigt wurden. Die Ergebnisse deuten darauf hin, dass Sprecher phonetische Details anpassen, um ein Gleichgewicht zwischen Informationsdichte und phonetischer Kodierung aufrechtzuerhalten.},
pubstate = {published},
type = {article}
}

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• 10.1515_ling-2024-0143     (0.65MB)
• https://www.degruyterbrill.com/document/doi/10.1515/ling-2024-0143/html
• https://doi.org/10.1515/ling-2024-0143

@article{haeuser_2025_subtlex,
title = {Not so SUBTLE(X): Word frequency estimates and their fit to sentential reading times in interaction with predictability},
author = {Katja H{\"a}user and Jutta Kray},
url = {https://www.degruyterbrill.com/document/doi/10.1515/ling-2024-0143/html},
doi = {https://doi.org/10.1515/ling-2024-0143},
year = {2025},
date = {2025},
journal = {Linguistics - An Interdisciplinary Journal of the Language Sciences},
abstract = {

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• xue25b_interspeech     (0.69MB)
• https://www.isca-archive.org/interspeech_2025/xue25b_interspeech.html
• https://doi.org/10.21437/Interspeech.2025-1676

@inproceedings{Xue/etal:2025a,
title = {The Effect of Word Predictability on Spoken Cross-Language Intelligibility},
author = {Wei Xue and Iuliia Zaitova and Bernd M{\"o}bius},
url = {https://www.isca-archive.org/interspeech_2025/xue25b_interspeech.html},
doi = {https://doi.org/10.21437/Interspeech.2025-1676},
year = {2025},
date = {2025},
booktitle = {Proceedings of Interspeech 2025},
issn = {2958-1796},
pages = {3798-3802},
address = {Rotterdam, The Netherlands},
abstract = {

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