Apparent Local Robustness Under Context-Reduced Interfaces: A Minimal Synthetic Stress Test

This technical note presents a minimal synthetic stress test on local robustness under reduced context interfaces in large language model inference. A controlled dataset of 100 multiple-choice instances is introduced across four evidence regimes: easy local retrieval, distributed evidence integration, conflict-sensitive update resolution, and position-sensitive retrieval. The same model is evaluated under three interfaces: FULL, RECENT, and a deterministic COMPRESSED interface retaining only the first sentence of each block. The main result is a clear regime-dependent dissociation: perfect local robustness is preserved in the easy regime, while strong interface-specific failures emerge outside it. The note is strictly diagnostic and local in scope, and argues that local benchmark robustness under a reduced context interface does not imply global behavioral equivalence across evidence regimes.