5 papers · 1 filter
MICA: Multivariate Infini Compressive Attention for Time Series Forecasting
Willa Potosnak, Nina Żukowska, Michał Wiliński +4
Multivariate forecasting with Transformers faces a core scalability challenge: modeling cross-channel dependencies via attention compounds attention's quadratic sequence complexity…
Investigating Compositional Reasoning in Time Series Foundation Models
Willa Potosnak, Cristian Challu, Mononito Goswami +4
Large pre-trained time series foundation models (TSFMs) have demonstrated promising zero-shot performance across a wide range of domains. However, a question remains: Do TSFMs succ…
Towards Long-Context Time Series Foundation Models
Nina Żukowska, Mononito Goswami, Michał Wiliński +2
Time series foundation models have shown impressive performance on a variety of tasks, across a wide range of domains, even in zero-shot settings. However, most of these models are…
Exploring Representations and Interventions in Time Series Foundation Models
Michał Wiliński, Mononito Goswami, Willa Potosnak +2
Time series foundation models (TSFMs) promise to be powerful tools for a wide range of applications. However, their internal representations and learned concepts are still not well…
Implicit Reasoning in Deep Time Series Forecasting
Willa Potosnak, Cristian Challu, Mononito Goswami +3
Recently, time series foundation models have shown promising zero-shot forecasting performance on time series from a wide range of domains. However, it remains unclear whether thei…