SpecTM: Spectral Targeted Masking for Trustworthy Foundation Models
Foundation models are now increasingly being developed for Earth observation (EO), yet they often rely on stochastic masking that do not explicitly enforce physics constraints; a critical trustworthiness limitation, in particular for predictive models that guide public health decisions. In this work, we propose SpecTM (Spectral Targeted Masking), a physics-informed masking design that encourages the reconstruction of targeted bands from cross-spectral context during pretraining. To achieve this, we developed an adaptable multi-task (band reconstruction, bio-optical index inference, and 8-day-ahead temporal prediction) self-supervised learning (SSL) framework that encodes spectrally intrin...
| Authors | Syed Usama Imtiaz, Mitra Nasr Azadani, Nasrin Alamdari |
|---|---|
| Primary category | cs.AI |
| Published | 23 March 2026 |
| Last updated at source | 3 May 2026 |
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