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Sinhala language semantic change analyzed with Llama-3.1-8B

Researchers have developed a computational framework to analyze the diachronic semantic change in the Sinhala language, spanning from the 13th to the 20th century. The study utilized both static embeddings (Word2Vec, FastText) and contextualized embeddings from a fine-tuned Llama-3.1-8B model. Findings indicate that semantic drift is not uniform but is significantly influenced by a smaller subset of high-impact contextual instances, rather than a gradual, widespread shift. AI

IMPACT Provides a framework for diachronic analysis in low-resource languages, potentially improving historical linguistics tools.

RANK_REASON Academic paper detailing a new computational framework for analyzing semantic change in a low-resource language. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Sinhala language semantic change analyzed with Llama-3.1-8B

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Academic paper detailing a new computational framework for analyzing semantic change in a low-resource language. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Nevidu Jayatilleke, Nisansa de Silva ·

    Dynamics of meaning: Towards the Evaluation of Diachronic Semantic Change in Sinhala

    arXiv:2609.08609v2 Announce Type: replace Abstract: Tracking semantic change in low-resource languages across extensive historical timelines presents significant challenges due to data scarcity and the limitations of static embedding alignments. This study investigates the diachr…