TiRex-2 is a recurrent xLSTM time series foundation model for multivariate forecasting with future covariates and constant-cost streaming that reports SOTA zero-shot results on GIFT-Eval and fev-bench.
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Pith papers citing it
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2026 3verdicts
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NSTM maps European bidding zones into a network via metric graph and neighborhood measure, outperforming independent local models in day-ahead price forecasting across 39 zones.
Normalization choice significantly influences training convergence and forecasting performance in causal large time-series models.
citing papers explorer
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TiRex-2: Generalizing TiRex to Multivariate Data and Streaming
TiRex-2 is a recurrent xLSTM time series foundation model for multivariate forecasting with future covariates and constant-cost streaming that reports SOTA zero-shot results on GIFT-Eval and fev-bench.
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Does Normalization Choice Matter for Causal Large Time-Series Models?
Normalization choice significantly influences training convergence and forecasting performance in causal large time-series models.