gift-eval-8e231327·2 events·first seen Aliases: GIFT-Eval
TiRex-2 is a recurrent xLSTM-based time series foundation model that extends the univariate TiRex to multivariate forecasting with past and future covariates, while supporting streaming inference at constant per-patch cost. The model uses a bidirectional time mixer and asymmetric grouped-attention variate mixer to handle future-known covariates without violating causality over target variables. A synthetic coupling pipeline enables scalable multivariate pretraining from univariate corpora. TiRex-2 claims state-of-the-art zero-shot performance on GIFT-Eval and fev-bench benchmarks with 38.4M–82.5M parameters depending on mode.
Datadog releases Toto 2.0, a family of five open-weights time series forecasting models ranging from 4M to 2.5B parameters, demonstrating consistent forecast quality improvements with scale. The models achieve state-of-the-art results on three benchmarks: BOOM (observability), GIFT-Eval (general-purpose), and TIME (contamination-resistant). The release includes architectural details, a u-muP hyperparameter transfer pipeline, and all base checkpoints under Apache 2.0 license.