RAVEN proposes a regime-aware MoE architecture with cumulative importance thresholding and correlation-aware weighting to adaptively select temporal context for non-stationary financial forecasting.
arXiv preprint arXiv:2603.11352 , year=
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Adaptive patching for time-series Transformers yields no consistent gain over a tuned uniform baseline on long-horizon benchmarks once evaluated with fixed backbones.
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Adaptive Patching Is Harder Than It Looks For Time-Series Forecasting
Adaptive patching for time-series Transformers yields no consistent gain over a tuned uniform baseline on long-horizon benchmarks once evaluated with fixed backbones.