arXiv Artificial Intelligence

EXAONE Finance 1.0: An Attention-free Time Series Foundation Model for Financial Time Series

1 day ago 10.09.2026 07:00 👁 1 views
EXAONE Finance 1.0: An Attention-free Time Series Foundation Model for Financial Time Series

Quick summary

arXiv:2609.04239v2 Announce Type: replace Abstract: This technical report presents EXAONE Forecast for Finance (EXAONE Finance), a financial time series foundation model (TSFM) tailored to financial forecasting. While recent TSFMs achieve strong zero-shot performance through large-scale pretraining, they are primarily developed for general-domain time series and largely rely on self-attention backbones whose computational cost grows quadratically with sequence length and variate count. Moreover, they assume fully observed inputs and are pretrained on corpora that fail to adequately capture the

Key takeaways

  • arXiv:2609.04239v2 Announce Type: replace Abstract: This technical report presents EXAONE Forecast for Finance (EXAONE Finance), a financial time series foundation model (TSFM) tailored to financial forecasting.
  • While recent TSFMs achieve strong zero-shot performance through large-scale pretraining, they are primarily developed for general-domain time series and largely rely on self-attention backbones whose computational cost grows quadratically with sequence length and variate count.
  • Moreover, they assume fully observed inputs and are pretrained on corpora that fail to adequately capture the

Why it matters

“EXAONE Finance 1.0: An Attention-free Time Series Foundation Model for Financial Time Series” should be evaluated beyond branding and benchmark scores. Its practical importance will emerge in task accuracy, latency, unit cost, safety and integration with real workflows.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗