GIFT-Eval
PulseAugur coverage of GIFT-Eval — every cluster mentioning GIFT-Eval across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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FlowState Model Achieves Sampling-Rate-Equivariant Time-Series Forecasting
Researchers have introduced FlowState, a new time-series foundation model designed for enhanced adaptability and efficiency. Unlike previous transformer-based models, FlowState utilizes a state space model encoder paire…
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New MoE frameworks enhance time series forecasting efficiency and accuracy
Researchers have developed new Mixture-of-Experts (MoE) frameworks for time series forecasting that aim to improve efficiency and accuracy. AME-TS uses structure-guided routing to align expert specialization with tempor…
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Toto 2.0 models show scaling benefits in time series forecasting
Researchers have introduced Toto 2.0, a suite of five open-weight time series forecasting models that demonstrate the effectiveness of scaling foundation models. The models, trained using a single recipe, show improved …