Papers by George-Andrei Dima

2 papers
RoQLlama: A Lightweight Romanian Adapted Language Model (2024.findings-emnlp)

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Challenge: Currently, open-source large language models are limited to tasks involving the English language.
Approach: They propose to use QLoRA to train a Romanian-adapted LLM with 7 billion parameters and quantized to 4 bits to improve model's performance.
Outcome: The proposed model outperforms the other LLMs on four out of the seven tasks investigated using zero-shot prompting.
EENLP: Cross-lingual Eastern European NLP Index (2022.lrec-1)

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Challenge: Existing NLP resources for Eastern European languages are sparse.
Approach: They propose to use existing Eastern European language resources to build cross-lingual datasets for five different semantic tasks to support commonsense reasoning.
Outcome: The proposed model trains on 104 languages and shows impressive results on text analysis tasks.

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