StateFlow extends VARNN with dual hidden and residual-memory states plus a chunk decoder and two-stage training to enable competitive long-horizon time series forecasting while retaining a compact recurrent design.
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Signed Dual Attention is a parameter-free attention module that models signed dependencies in time series via dual message passing to achieve two-head expressiveness in one block.
citing papers explorer
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StateFlow: Dual-State Recurrent Modeling for Long-Horizon Time Series Forecasting
StateFlow extends VARNN with dual hidden and residual-memory states plus a chunk decoder and two-stage training to enable competitive long-horizon time series forecasting while retaining a compact recurrent design.
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Signed Dual Attention: Capturing Signed Dependencies in Time Series Forecasting
Signed Dual Attention is a parameter-free attention module that models signed dependencies in time series via dual message passing to achieve two-head expressiveness in one block.