AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling
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Abstract (arXiv)
This paper describes the organization and findings of AXOLOTL'24, the first multilingual explainable semantic change modeling shared task. We present new sense-annotated diachronic semantic change datasets for Finnish and Russian which were employed in the shared task, along with a surprise test-only German dataset borrowed from an existing source. The setup of AXOLOTL'24 is new to the semantic change modeling field, and involves subtasks of identifying unknown (novel) senses and providing dictionary-like definitions to these senses. The methods of the winning teams are described and compared, thus paving a path towards explainability in computational approaches to historical change of meaning.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 23 of its 47 references that are in the map. First posted on arXiv 4 Jul 2024.
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23 of 47 references.
References · 23
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11 more
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Citing papers per year: 2024: 2; 2025: 0; 2026: 1.
3 papers.