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README.md
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1) **Open-ended questions**, where the model will generate the definition of the target word;
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2) **Closed-ended questions**, where the model will generate the identifier of the correct option out of a list of alternatives.
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More details regarding the training procedure (e.g. hyperparameters, dataset construction, and so on) can be found in Section 4.2 of the [paper].
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- **Developed by:** Pierpaolo Basile, Lucia Siciliani, Elio Musacchio
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- **Model type:** LLaMA 3.1 Instruct
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If you use this model in your research, please cite the following:
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```bibtex
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```
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## Instructions
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1) **Open-ended questions**, where the model will generate the definition of the target word;
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2) **Closed-ended questions**, where the model will generate the identifier of the correct option out of a list of alternatives.
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More details regarding the training procedure (e.g. hyperparameters, dataset construction, and so on) can be found in Section 4.2 of the [paper](https://arxiv.org/abs/2503.08662).
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- **Developed by:** Pierpaolo Basile, Lucia Siciliani, Elio Musacchio
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- **Model type:** LLaMA 3.1 Instruct
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If you use this model in your research, please cite the following:
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```bibtex
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@misc{basile2025exploringwordsensedisambiguation,
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title={Exploring the Word Sense Disambiguation Capabilities of Large Language Models},
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author={Pierpaolo Basile and Lucia Siciliani and Elio Musacchio and Giovanni Semeraro},
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year={2025},
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eprint={2503.08662},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2503.08662},
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}
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```
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## Instructions
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