title: Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance
summary: 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.
paper_authors._id: 67bfc297ca6e3c22b6d99c78
paper_authors.name: Xueqing Peng
paper_authors._id: 67bfc297ca6e3c22b6d99c79
paper_authors.name: Triantafillos Papadopoulos
paper_authors._id: 67bfc297ca6e3c22b6d99c7a
paper_authors.name: Efstathia Soufleri
paper_authors._id: 67bfc297ca6e3c22b6d99c7b
paper_authors.name: Polydoros Giannouris
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-28T13:24:53.698Z
paper_authors._id: 673354dc5b8d4dccb4da9b63
paper_authors.avatarUrl: /avatars/ae6bd67a1d93fee89bf5c576fd8ddc39.svg
paper_authors.fullname: Polydoros Giannouris
paper_authors.type: user
paper_authors.user: PolydorosG
paper_authors._id: 67bfc297ca6e3c22b6d99c7c
paper_authors.name: Ruoyu Xiang
paper_authors._id: 67bfc297ca6e3c22b6d99c7d
paper_authors.name: Yan Wang
paper_authors._id: 67bfc297ca6e3c22b6d99c7e
paper_authors.name: Lingfei Qian
paper_authors._id: 67bfc297ca6e3c22b6d99c7f
paper_authors.name: Jimin Huang
paper_authors.status: extracted_pending
paper_authors.statusLastChangedAt: 2025-02-27T01:40:40.189Z
paper_authors._id: 63b58ed5889aa6707f0bb0f4
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/63b58ed5889aa6707f0bb0f4/znl74_aMswlV8VtHrfj3G.jpeg
paper_authors.fullname: Jimin Huang
paper_authors.type: user
paper_authors.user: jiminHuang
paper_authors._id: 67bfc297ca6e3c22b6d99c80
paper_authors.name: Qianqian Xie
paper_authors._id: 67bfc297ca6e3c22b6d99c81
paper_authors.name: Sophia Ananiadou
paper_title: Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance
paper_summary: 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.
paper_ai_keywords: large language models (LLMs) financial natural language processing (NLP) linguistic complexity named entity recognition question answering abstractive summarization topic classification Greek Financial Evaluation Benchmark (Plutus-ben) Greek Financial LLM (Plutus-8B) Greek domain-specific data Greek financial datasets cross-lingual transfer financial reasoning gaps