AI RESEARCH
How Much of a Model Do We Need? Redundancy and Slimmability in Remote Sensing Foundation Models
arXiv CS.CV
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ArXi:2601.22841v2 Announce Type: replace Large-scale foundation models (FMs) in remote sensing (RS) (denoted as RS FMs) are developed following paradigms established in computer vision (CV), yet the validity of transferring CV scaling laws to RS has not been systematically examined. We hypothesize that RS FMs enter an overparameterized regime at substantially smaller scales than their CV counterparts, with task-relevant information encoded redundantly across model dimensions.