RATL: Learning from Retrieved Residuals for Robust Multivariate Time-Series Forecasting

arXiv:2609.03937 · cs.LG, cs.AI · Submitted 2026-09-03 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-03

Updated: 2026-09-03

Terminology

• Transformer — 8× in this paper · explained in 2 episodes
• Time Series Forecasting — 7× in this paper · explained in 3 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Ablation — 1× in this paper · explained in 1 episode
• Abstention — 1× in this paper · explained in 1 episode
• Admissibility — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 16 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Transferability — 1× in this paper · explained in 4 episodes

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