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DIBench: Benchmarking Decision Integrity of GUI-based Mobile Agents Under Deceptive Injections
As GUI-based mobile agents rapidly progress, rigorous safety evaluation of their autonomous decision-making in realistic app interfaces becomes increasingly critical. Existing benchmarks mainly focus on execution-level anomalies using task success or hijack rates, but fail to capture the in-task goa
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