Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance

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Hauptverfasser: Peng, Xueqing, Papadopoulos, Triantafillos, Soufleri, Efstathia, Giannouris, Polydoros, Xiang, Ruoyu, Wang, Yan, Qian, Lingfei, Huang, Jimin, Xie, Qianqian, Ananiadou, Sophia
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Veröffentlicht: 2025
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author Peng, Xueqing
Papadopoulos, Triantafillos
Soufleri, Efstathia
Giannouris, Polydoros
Xiang, Ruoyu
Wang, Yan
Qian, Lingfei
Huang, Jimin
Xie, Qianqian
Ananiadou, Sophia
author_facet Peng, Xueqing
Papadopoulos, Triantafillos
Soufleri, Efstathia
Giannouris, Polydoros
Xiang, Ruoyu
Wang, Yan
Qian, Lingfei
Huang, Jimin
Xie, Qianqian
Ananiadou, Sophia
contents Despite Greece's pivotal role in the global economy, large language models (LLMs) remain underexplored for Greek financial context due to the linguistic complexity of Greek and the scarcity of domain-specific datasets. Previous efforts in multilingual financial natural language processing (NLP) have exposed considerable performance disparities, yet no dedicated Greek financial benchmarks or Greek-specific financial LLMs have been developed until now. To bridge this gap, we introduce Plutus-ben, the first Greek Financial Evaluation Benchmark, and Plutus-8B, the pioneering Greek Financial LLM, fine-tuned with Greek domain-specific data. Plutus-ben addresses five core financial NLP tasks in Greek: numeric and textual named entity recognition, question answering, abstractive summarization, and topic classification, thereby facilitating systematic and reproducible LLM assessments. To underpin these tasks, we present three novel, high-quality Greek financial datasets, thoroughly annotated by expert native Greek speakers, augmented by two existing resources. Our comprehensive evaluation of 22 LLMs on Plutus-ben reveals that Greek financial NLP remains challenging due to linguistic complexity, domain-specific terminology, and financial reasoning gaps. These findings underscore the limitations of cross-lingual transfer, the necessity for financial expertise in Greek-trained models, and the challenges of adapting financial LLMs to Greek text. We release Plutus-ben, Plutus-8B, and all associated datasets publicly to promote reproducible research and advance Greek financial NLP, fostering broader multilingual inclusivity in finance.
format Preprint
id arxiv_https___arxiv_org_abs_2502_18772
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance
Peng, Xueqing
Papadopoulos, Triantafillos
Soufleri, Efstathia
Giannouris, Polydoros
Xiang, Ruoyu
Wang, Yan
Qian, Lingfei
Huang, Jimin
Xie, Qianqian
Ananiadou, Sophia
Computation and Language
Despite Greece's pivotal role in the global economy, large language models (LLMs) remain underexplored for Greek financial context due to the linguistic complexity of Greek and the scarcity of domain-specific datasets. Previous efforts in multilingual financial natural language processing (NLP) have exposed considerable performance disparities, yet no dedicated Greek financial benchmarks or Greek-specific financial LLMs have been developed until now. To bridge this gap, we introduce Plutus-ben, the first Greek Financial Evaluation Benchmark, and Plutus-8B, the pioneering Greek Financial LLM, fine-tuned with Greek domain-specific data. Plutus-ben addresses five core financial NLP tasks in Greek: numeric and textual named entity recognition, question answering, abstractive summarization, and topic classification, thereby facilitating systematic and reproducible LLM assessments. To underpin these tasks, we present three novel, high-quality Greek financial datasets, thoroughly annotated by expert native Greek speakers, augmented by two existing resources. Our comprehensive evaluation of 22 LLMs on Plutus-ben reveals that Greek financial NLP remains challenging due to linguistic complexity, domain-specific terminology, and financial reasoning gaps. These findings underscore the limitations of cross-lingual transfer, the necessity for financial expertise in Greek-trained models, and the challenges of adapting financial LLMs to Greek text. We release Plutus-ben, Plutus-8B, and all associated datasets publicly to promote reproducible research and advance Greek financial NLP, fostering broader multilingual inclusivity in finance.
title Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance
topic Computation and Language
url https://arxiv.org/abs/2502.18772