contextual modeling 1data augmentation 1multimodal learning 1synthetic datasets 1time series forecasting 1
From the 1 of 2 linked papers with an AI index.
2 papers
cs.LG2026
Overcoming the Modality Gap in Context-Aided Forecasting
Vincent Zhihao Zheng, Ãtienne Marcotte, Arjun Ashok +4
The paper introduces a semi‑synthetic data augmentation technique to create high‑quality contextual information for time‑series forecasting, producing a 7 million‑sample dataset (C…
cs.AI2026
Dr-CiK: A Testbed for Foresight-Driven Agents
Yihong Tang, Andrew Robert Williams, Arjun Ashok +6
Time series forecasting in real-world settings often depends not only on historical observations, but also on external context that must be actively discovered from noisy, heteroge…