Data and Model Checkpoints from: ExoPrompt: Transformer-based greenhouse climate forecasting with structured conditioning and physics-based simulation
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Data and model checkpoints accompanying the paper: Soykan et al. (2026). ExoPrompt: Transformer-based greenhouse climate forecasting with structured conditioning and physics-based simulation. Computers and Electronics in Agriculture, 246, 111673. https://doi.org/10.1016/j.compag.2026.111673 --- Data --- new_world_sim.zipSynthetic GreenLight simulation outputs used for pretraining. Covers 9 parameter scenarios across 15 geographic locations and 2 lighting modes (LED/HPS). Each runincludes paired .csv time-series and .json exogenous parameter files. gt.zipGround-truth climate measurements from a tomato greenhouse trial (Bleiswijk, 2009-2010) under LED and HPS lighting, reorganised into CSV format for use withthe ExoPrompt training pipeline. c_leakage_gt_led_conditions_csv.zipSimulation sweeps varying a single exogenous parameter (cLeakage) with aligned ground-truth subsets, used for the controlled robustness experiment in Section 3.3. --- Model Checkpoints --- ckpts_pretrained_main.zipPretrained ExoPrompt and Vanilla backbones evaluated zero-shot on ground truth (Table 4). ckpts_200k_main.zipFine-tuned checkpoints for mixed, LED-only, and HPS-only splits (Figure 5). …
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