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@@ -82,10 +82,18 @@ For more examples, see the GitHub repository [Historical Word Usage Generation](
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  ### Citation
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  If you use Janus, please cite:
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  ```
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- @article{Cassotti2024Janus,
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- author = {Pierluigi Cassotti and Nina Tahmasebi},
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- title = {Sense-specific Historical Word Usage Generation},
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- journal = {TACL},
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- year = {2025}
 
 
 
 
 
 
 
 
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  }
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  ```
 
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  ### Citation
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  If you use Janus, please cite:
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  ```
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+ @article{10.1162/tacl_a_00761,
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+ author = {Cassotti, Pierluigi and Tahmasebi, Nina},
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+ title = {Sense-specific Historical Word Usage Generation},
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+ journal = {Transactions of the Association for Computational Linguistics},
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+ volume = {13},
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+ pages = {690-708},
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+ year = {2025},
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+ month = {07},
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+ abstract = {Large-scale sense-annotated corpora are important for a range of tasks but are hard to come by. Dictionaries that record and describe the vocabulary of a language often offer a small set of real-world example sentences for each sense of a word. However, on their own, these sentences are too few to be used as diachronic sense-annotated corpora. We propose a targeted strategy for training and evaluating generative models producing historically and semantically accurate word usages given any word, sense definition, and year triple. Our results demonstrate that fine-tuned models can generate usages with the same properties as real-world example sentences from a reference dictionary. Thus the generated usages will be suitable for training and testing computational models where large-scale sense-annotated corpora are needed but currently unavailable.},
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+ issn = {2307-387X},
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+ doi = {10.1162/tacl_a_00761},
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+ url = {https://doi.org/10.1162/tacl\_a\_00761},
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+ eprint = {https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl\_a\_00761/2535111/tacl\_a\_00761.pdf},
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  }
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  ```