الملخص
Time-series foundation models (TSFMs) have achieved strong forecasting performance across domains. However, most adaptation methods remain static. Existing all-in-one methods learn a single set of dataset-level parameter updates and apply the same adapted model to every input. As a result, they cannot adapt the model parameters to the temporal patterns, seasonality and dynamics of each input time series. This limits their ability to produce forecasts that are tailored to heterogeneous inputs. To address this limitation, we propose AdaCast, a conditional parameter generation framework for time-series forecasting. AdaCast uses a generator to produce input-specific low-rank parameter updates for a frozen pretrained TSFM. These updates adapt the model to each input during both training and inference. Across six public benchmarks, AdaCast consistently outperforms static adaptation baseline in in-domain forecasting and improves zero-shot generalization to held-out datasets across domains. These results demonstrate that conditional parameter generation provides an effective approach for adaptive forecasting.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Nallagatla, D., Jacob, D. C., & He, P. (2026). AdaCast: Conditional Parameter Generation for Adaptive Time Series Forecasting. https://omanscience.com/ar/articles/adacast-conditional-parameter-generation-for-adaptive-time-series-forecasting
MLA 9
Nallagatla, Darahaas, et al. "AdaCast: Conditional Parameter Generation for Adaptive Time Series Forecasting." https://omanscience.com/ar/articles/adacast-conditional-parameter-generation-for-adaptive-time-series-forecasting.
شيكاغو (المؤلف–التاريخ)
Nallagatla, Darahaas, Darryl Cherian Jacob, and Pan He. 2026. "AdaCast: Conditional Parameter Generation for Adaptive Time Series Forecasting." https://omanscience.com/ar/articles/adacast-conditional-parameter-generation-for-adaptive-time-series-forecasting.
هارفارد
Nallagatla, D., Jacob, D. C. and He, P. (2026) 'AdaCast: Conditional Parameter Generation for Adaptive Time Series Forecasting', Available at: https://omanscience.com/ar/articles/adacast-conditional-parameter-generation-for-adaptive-time-series-forecasting.
فانكوفر
Nallagatla D, Jacob DC, He P. AdaCast: Conditional Parameter Generation for Adaptive Time Series Forecasting. https://omanscience.com/ar/articles/adacast-conditional-parameter-generation-for-adaptive-time-series-forecasting
IEEE
D. Nallagatla, D. C. Jacob, and P. He, "AdaCast: Conditional Parameter Generation for Adaptive Time Series Forecasting," https://omanscience.com/ar/articles/adacast-conditional-parameter-generation-for-adaptive-time-series-forecasting.