# A Dutch Financial Large Language Model

arXiv: https://arxiv.org/abs/2410.12835 · HTML: https://mlsanity.com/paper/2410.12835/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 36 references that are in the map.
- First posted on arXiv 3 Oct 2024.

## Builds on (most cited first, 22 of 22)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://mlsanity.com/paper/2305.18290/) (2023)
- [Finetuned Language Models Are Zero-Shot Learners](https://mlsanity.com/paper/2109.01652/) (2021)
- [FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness](https://mlsanity.com/paper/2205.14135/) (2022)
- [QLoRA: Efficient Finetuning of Quantized LLMs](https://mlsanity.com/paper/2305.14314/) (2023)
- [Self-Instruct: Aligning Language Models with Self-Generated Instructions](https://mlsanity.com/paper/2212.10560/) (2022)
- [Multitask Prompted Training Enables Zero-Shot Task Generalization](https://mlsanity.com/paper/2110.08207/) (2021)
- [BloombergGPT: A Large Language Model for Finance](https://mlsanity.com/paper/2303.17564/) (2023)
- [Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm](https://mlsanity.com/paper/2102.07350/) (2021)
- [Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts](https://mlsanity.com/paper/1307.5336/) (2013)
- [PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance](https://mlsanity.com/paper/2306.05443/) (2023)
- [Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback](https://mlsanity.com/paper/2307.16039/) (2023)
- [Impact of News on the Commodity Market: Dataset and Results](https://mlsanity.com/paper/2009.04202/) (2020)
- [FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets](https://mlsanity.com/paper/2310.04793/) (2023)
- [BBT-Fin: Comprehensive Construction of Chinese Financial Domain Pre-trained Language Model, Corpus and Benchmark](https://mlsanity.com/paper/2302.09432/) (2023)
- [Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese](https://mlsanity.com/paper/2110.06696/) (2021)
- [FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models](https://mlsanity.com/paper/2402.10986/) (2024)
- [What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis](https://mlsanity.com/paper/2212.11311/) (2022)
- [Language Resources for Dutch Large Language Modelling](https://mlsanity.com/paper/2312.12852/) (2023)
- [Sequence-Based Extractive Summarisation for Scientific Articles](https://mlsanity.com/paper/2204.03301/) (2022)
- [TopoLedgerBERT: Topological Learning of Ledger Description Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/2407.05175/) (2024)

## Built on by (most cited first, 2 of 2)

- [Advancing Financial Engineering with Foundation Models: Progress, Applications, and Challenges](https://mlsanity.com/paper/2507.18577/) (2025)
- [TULIP: Adapting Open-Source Large Language Models for Underrepresented Languages and Specialized Financial Tasks](https://mlsanity.com/paper/2508.16243/) (2025)

## Abstract (arXiv)

This paper presents FinGEITje, the first Dutch financial Large Language Model (LLM) specifically designed and optimized for various financial tasks. Together with the model, we release a specialized Dutch financial instruction tuning dataset with over 140,000 samples, constructed employing an automated translation and data processing method. The open-source data construction method is provided, facilitating the creation of financial instruction datasets in different languages. To evaluate model performance, the study introduces the first Dutch financial evaluation benchmark, along with an automated evaluation method that utilizes an LLM as an independent evaluator, reducing manual intervention in performance evaluation. The experimental results highlight the superior performance of FinGEITje across five critical Dutch and English financial tasks.