Presents TRACE, a training-free framework for GUI agents that reduces inference latency and memory from accumulated high-resolution screenshots via visual token pruning. Combines layout-derived interaction priors with instruction relevance and feature novelty to rank visual evidence, reserving budget for native visual tokens while applying monotone KV contraction to keep cache reuse consistent across a trajectory. Evaluated across six GUI benchmarks and multiple models.
