An interpretable deep learning framework with a new tokenizer is used to quantify how grammatical gender information is distributed between lemmas and sentential context during the Latin-to-Occitan transition.
Improving Lemmatization of Non-Standard Languages with Joint Learning
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
LLM-based POS tagging outperforms traditional taggers on medieval Occitan, Catalan, and French, with fine-tuning and cross-lingual transfer providing the largest gains for under-resourced varieties.
citing papers explorer
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Lost in Translation? Exploring the Shift in Grammatical Gender from Latin to Occitan
An interpretable deep learning framework with a new tokenizer is used to quantify how grammatical gender information is distributed between lemmas and sentential context during the Latin-to-Occitan transition.
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From Traditional Taggers to LLMs: A Comparative Study of POS Tagging for Medieval Romance Languages
LLM-based POS tagging outperforms traditional taggers on medieval Occitan, Catalan, and French, with fine-tuning and cross-lingual transfer providing the largest gains for under-resourced varieties.