# RKEFino1: A Regulation Knowledge-Enhanced Large Language Model

arXiv: https://arxiv.org/abs/2506.05700 · HTML: https://mlsanity.com/paper/2506.05700/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 15 references that are in the map.
- First posted on arXiv 6 Jun 2025.

## Builds on (most cited first, 11 of 11)

- [BloombergGPT: A Large Language Model for Finance](https://mlsanity.com/paper/2303.17564/) (2023)
- [FinGPT: Open-Source Financial Large Language Models](https://mlsanity.com/paper/2306.06031/) (2023)
- [PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance](https://mlsanity.com/paper/2306.05443/) (2023)
- [A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methods](https://mlsanity.com/paper/2403.02901/) (2024)
- [FiNER: Financial Numeric Entity Recognition for XBRL Tagging](https://mlsanity.com/paper/2203.06482/) (2022)
- [Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications](https://mlsanity.com/paper/2408.11878/) (2024)
- [Automate Strategy Finding with LLM in Quant Investment](https://mlsanity.com/paper/2409.06289/) (2024)
- [Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance](https://mlsanity.com/paper/2502.18772/) (2025)
- [Financial Numeric Extreme Labelling: A Dataset and Benchmarking for XBRL Tagging](https://mlsanity.com/paper/2306.03723/) (2023)
- [CDEMapper: Enhancing NIH Common Data Element Normalization using Large Language Models](https://mlsanity.com/paper/2412.00491/) (2024)
- [OrdRankBen: A Novel Ranking Benchmark for Ordinal Relevance in NLP](https://mlsanity.com/paper/2503.00674/) (2025)

## Built on by (most cited first, 1 of 1)

- [Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environment](https://mlsanity.com/paper/2603.23638/) (2026)

## Abstract (arXiv)

Recent advances in large language models (LLMs) hold great promise for financial applications but introduce critical accuracy and compliance challenges in Digital Regulatory Reporting (DRR). To address these issues, we propose RKEFino1, a regulation knowledge-enhanced financial reasoning model built upon Fino1, fine-tuned with domain knowledge from XBRL, CDM, and MOF. We formulate two QA tasks-knowledge-based and mathematical reasoning-and introduce a novel Numerical NER task covering financial entities in both sentences and tables. Experimental results demonstrate the effectiveness and generalization capacity of RKEFino1 in compliance-critical financial tasks. We have released our model on Hugging Face.