Scaling Laws in Financial Foundation Models: Optimizing Data Efficiency
Published:Dec 13, 2025 16:28
•1 min read
•ArXiv
Analysis
This ArXiv paper likely explores how continued pretraining impacts the performance of financial foundation models, focusing on data efficiency. The research offers insights into scaling laws, which could inform more effective model development in finance.
Key Takeaways
- •Investigates the relationship between continued pretraining and financial model performance.
- •Applies scaling laws to optimize data usage in financial foundation models.
- •Provides insights into building more efficient and effective AI models for finance.
Reference
“The paper examines the data efficiency frontier of financial foundation models.”