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Author

B. Pavlyshenko

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Open access Sep 2026

Fine-Tuning Large Language Models for Financial Applications Using Direct Preference Optimization

Large language models have changed natural language processing across many fields, but their general-purpose design limits performance in specialized domains like finance. This study examines the adaptation of Meta-Llama-3-8B-Instruct for financial NLP tasks through parameter-efficient fine-tuning methods and direct pr...

B. Pavlyshenko, I. Bulka · 0 citations
#artificial intelligence Preprint Sep 2026

QLoRA Fine-Tuning of Ministral LLM for Sequence-to-Function Protein Annotation

QLoRA-fine-tuned compact LLMs can generate curator-style annotations with genuine biological value for a substantial subset of proteins, and is concluded that QLoRA-fine-tuned compact LLMs can generate curator-style annotations with genuine biological value for a substantial subset of proteins.

Demian Pavlyshenko, B. Pavlyshenko · 0 citations

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