A multimodal forecasting framework that combines a retrieval-augmented temporal learner with frozen VLM embeddings of generated images and text, tested on seven benchmark datasets.
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Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
A multimodal forecasting framework that combines a retrieval-augmented temporal learner with frozen VLM embeddings of generated images and text, tested on seven benchmark datasets.