Parameter-Efficient Adaptation of Pretrained Language Models for Time-Series Forecasting
Results indicate that freezing the pretrained backbone and training lightweight projection and adapter modules provides a favourable accuracy--efficiency trade-off with stable behaviour across varying context lengths.