Author

Geremia Pompei

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#machine learning Preprint Sep 2026

OpenTSLM TeeMoE: A Unified Time-Series Language Model for Forecasting, Contextual Prediction, and Reasoning

OpenTSLM TeeMoE is introduced, a generalist time-series language model that can forecast directly from observed time series, reason over textual context and temporal patterns, and synthesize and refine predictions from external numerical forecasting specialists.

Tony Chen, Timo Stoffregen, Maxwell A. Xu et al. · 0 citations

Open access Sep 2026

On-board efficiency: comparing compressed deep learning and classical models for Earth observation

A unified experimental framework is introduced that jointly evaluates compressed deep learning models and CML ensembles on two representative EO benchmarks and provides empirical guidance for selecting model families and compression strategies when designing future on-board EO systems.

G. Di Palma, Alessio Pardini, Lan-Pei Li et al. · Pattern Analysis and Applica... · 0 citations