Papers by Pierluigi Cassotti
Analyzing Semantic Change through Lexical Replacements (2024.acl-long)
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| Challenge: | Modern language models can contextualize words based on their surrounding contexts, but semantic change can compromise this capability. |
| Approach: | They propose a replacement schema where a target word is replaced with lexical replacements of varying relatedness . they leverage the replacement schema as a basis for a novel interpretable model for semantic change . |
| Outcome: | The proposed model is the first to evaluate LLaMa for semantic change detection . it shows that lexical replacements can detect unexpected contexts . |
Towards Language-Agnostic STIPA: Universal Phonetic Transcription to Support Language Documentation at Scale (2025.emnlp-main)
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| Challenge: | Existing ASR systems focus on orthographic output for high-resource languages, but STIPA can be used as a language-agnostic interface for documenting under-resourced and unwritten languages. |
| Approach: | They propose to use the International Phonetic Alphabet (STIPA) to generate phonetic transcriptions using a language-agnostic interface. |
| Outcome: | The proposed model reduces phonetic error rates even in low-resource settings and can be used for documenting under-resourced and unwritten languages. |
Computational modeling of semantic change (2024.eacl-tutorials)
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| Challenge: | Languages change constantly over time, influenced by social, technological, cultural and political factors that affect how people express themselves. |
| Approach: | They propose to categorise the types of change, the causes and the mechanisms underlying the different types of changes using large diachronic corpora and evaluation benchmarks. |
| Outcome: | In historical linguistics, tools and methods have been developed to analyse the process . they include categorisations of types of change, causes and mechanisms . but traditional methods, while informative, are often based on small, carefully curated samples. |
More DWUGs: Extending and Evaluating Word Usage Graph Datasets in Multiple Languages (2024.emnlp-main)
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Dominik Schlechtweg, Pierluigi Cassotti, Bill Noble, David Alfter, Sabine Schulte Im Walde, Nina Tahmasebi
| Challenge: | Word Usage Graphs (WUGs) represent word sense clusters from simple pairwise word use judgments. |
| Approach: | They propose to use a weighted graph to represent human semantic proximity judgments for pairs of word uses to infer word sense clusters from simple pairwise word use judgments. |
| Outcome: | The proposed approach can be applied in a Word Sense Induction (WSI) setting or for Word sense disambiguation (WSD) it is the first and to date largest manually annotated, diachronic WUG dataset. |
TRoTR: A Framework for Evaluating the Re-contextualization of Text Reuse (2024.emnlp-main)
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| Challenge: | Existing methods for detecting text reuse focus on recontextualization . current approaches focus on text reuse across a diachronic corpus . |
| Approach: | They propose a framework that relies on topic relatedness for evaluating the diachronic change of context in which text is reused. |
| Outcome: | The proposed framework evaluates biblical text reuse human-annotated with topic relatedness . it exhibits greater sensitivity to textual similarity than topic relatedity, the authors show . |
Using Synchronic Definitions and Semantic Relations to Classify Semantic Change Types (2024.acl-long)
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| Challenge: | Existing models for detecting semantic change in corpora have been disregarded due to lack of knowledge of the nature of semantic change and the way it takes place. |
| Approach: | They propose a model that leverages synchronic lexical relations and definitions of word meanings to detect these types of change. |
| Outcome: | The proposed model can detect changes in a digitized version of Blank's dataset and improve human judgments of semantic relatedness and binary Lexical Semantic Change Detection. |
SenseRel: A Sense-Level Benchmark for Denotational and Connotational Meaning Relations (2026.acl-long)
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Pierluigi Cassotti, Naomi Baes, Stefano De Pascale, Jáder Martins Camboim de Sá, Francesco Periti, Nick Haslam, Dirk Geeraerts, Nina Tahmasebi
| Challenge: | Polysemy enables a single word to convey multiple related meanings . a word's sense is extended to new contexts and concepts, a process called semantic change is gradual . |
| Approach: | They propose a benchmark for modeling semantic relations between word senses . they use a model that distinguishes denotational and connotationally related aspects of meaning . |
| Outcome: | The proposed model is able to distinguish between denotational and connotationalist aspects of meaning . it is compared with models with GPT-4o, Llama 3.1, and DeepSeek . |
XL-LEXEME: WiC Pretrained Model for Cross-Lingual LEXical sEMantic changE (2023.acl-short)
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| Challenge: | Existing approaches to the Word in Context task use cross-encoders, which prevent the possibility of deriving comparable word embeddings. |
| Approach: | They propose a Lexical Semantic Change Detection model that extends SBERT, highlighting the target word in the sentence. |
| Outcome: | The proposed model outperforms the state-of-the-art on the multilingual benchmarks for SemEval-2020 Task 1 - Lexical Semantic Change (LSC) Detection and the RuShiftEval shared task. |
Elections go bananas: A First Large-scale Multilingual Study of Pluralia Tantum using LLMs (2026.eacl-long)
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| Challenge: | a large amount of annotated sentences for each feature can be used for in-depth analysis. |
| Approach: | They propose an annotation framework for lexicalization of pluralia tantum . they use an LLM to annotate each instance from the reference corpus . |
| Outcome: | The proposed framework provides useful annotators for semantic, syntactic and sense categories with accuracy ranging from 51% to 89% on a hand-annotated testset. |