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cs.CL2025
Towards Interpretable Time Series Foundation Models
Matthieu Boileau, Philippe Helluy, Jeremy Pawlus +1
In this paper, we investigate the distillation of time series reasoning capabilities into small, instruction-tuned language models as a step toward building interpretable time seri…
cs.CL2025
AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation
Elizabeth Fons, Elena Kochkina, Rachneet Kaur +5
This paper explores the potential of large language models (LLMs) to generate financial reports from time series data. We propose a framework encompassing prompt engineering, model…