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@incollection{tahmasebi-etal-2026-computational-364255,
title = {Computational Models of Semantic Change},
abstract = {This chapter provides an overview of key considerations when using computational methods to scan digital text for evidence of semantic change. It lays out the foundations of the field, from the distributional hypothesis to the methods employed and the resources available. It also shows how the computational study of semantic change relates to and supplements the corresponding field of historical linguistics. Computational approaches to semantic change are a relatively new field of study where much remains to be done. Therefore, we end by discussing future research directions and possible extensions of the field to address changing cultural and societal phenomena encoded in text.},
booktitle = {The Wiley Blackwell Companion to Diachronic and Historical Linguistics},
author = {Tahmasebi, Nina and Kutuzov, Andrey and Dubossarsky, Haim and Giulianelli, Mario},
year = {2026},
publisher = {Wiley Blackwell },
ISBN = {9781119898016},
pages = {1--34},
}
@inProceedings{cassotti-etal-2026-senserel-364254,
title = {SenseRel: A Sense-Level Benchmark for Denotational and Connotational Meaning Relations},
abstract = {Polysemy enables a single word to convey multiple related meanings, reflecting the conceptual and emotional aspects of the evolution of the senses. We introduce the first sense-level benchmark, SenseRel, for modeling semantic relations between word senses, uniting denotational and connotational aspects of meaning. SenseRel distinguishes denotational relations, such as generalization or metaphor, as well as two connotational dimensions: valence and arousal. We evaluate large language models (LLMs), GPT-4o, Llama 3.1, and DeepSeek, in zero-shot and fine-tuned settings. Results show that GPT-4o best aligns with human affective judgments, while a fine-tuned RoBERTa model excels at classifying denotational relations.},
booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
author = {Cassotti, Pierluigi and Baes, Naomi and De Pascale, Stefano and Martins Camboim de Sá, Jáder and Periti, Francesco and Haslam, Nick and Geeraerts, Dirk and Tahmasebi, Nina},
year = {2026},
publisher = {ACL},
pages = {499–515},
}
@inProceedings{spaziani-etal-2026-elections-361523,
title = {Elections go bananas: A First Large-scale Multilingual Study of Pluralia Tantum using LLMs},
abstract = {In this paper, we study the expansion of pluralia tantum, i.e., defective nouns which lack a singular form, like scissors. We base our work on an annotation framework specifically developed for the study of lexicalization of pluralia tantum, namely Lexicalization profiles. On a corresponding hand-annotated testset, we show that the OpenAI and DeepSeek models provide useful annotators for semantic, syntactic and sense categories, with accuracy ranging from 51% to 89%, averaged across all feature groups and languages. Next, we turn to a large-scale investigation of pluralia tantum. Using dictionaries, we extract candidate words for Italian, Russian and English and keep those for which the changing ratio of singular and plural form is evident in a corresponding reference corpus. We use an LLM to annotate each instance from the reference corpora according to the annotation framework. We show that the large amount of automatically annotated sentences for each feature can be used to perform in-depth linguistic analysis. Focusing on the correlation between an annotated feature and the grammatical form (singular vs. plural), patterns of morpho-semantic change are noted.},
booktitle = {Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, March 24–29, 2026, Rabat, Morocco (Volume 1: Long Papers) / Vera Demberg, Kentaro Inui, Lluís Marquez (eds.)},
author = {Spaziani, Elena and Zeinalipour, Kamyar and Cassotti, Pierluigi and Tahmasebi, Nina},
year = {2026},
publisher = {Association for Computational Linguistics},
address = {Kerrville, USA},
ISBN = {979-8-89176-380-7},
pages = {6547–6570},
}
@misc{tahmasebi-etal-2026-proceedings-361521,
title = {The Proceedings for the 6th International Workshop on Computational Approaches to Language Change (LChange’26)},
author = {Tahmasebi, Nina and Cassotti, Pierluigi and Montariol, Syrielle and Kutuzov, Andrey and Hibsher, Netta and Spaziani, Elena and Baes, Naomi},
year = {2026},
publisher = {Association for Computational Linguistics},
ISBN = {979-8-89176-362-3},
}