Empirical study finds background semantics, random pruning, and recency-based allocation improve token efficiency for GUI visual agents.
Global compression commander: Plug-and-play inference acceleration for high-resolution large vision-language models
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Rethinking Token Pruning for Historical Screenshots in GUI Visual Agents: Semantic, Spatial, and Temporal Perspectives
Empirical study finds background semantics, random pruning, and recency-based allocation improve token efficiency for GUI visual agents.