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Across widely adopted grounding benchmarks and navigation benchmarks spanning multiple platforms, LLaDA-UI substantially outperforms Qwen2.5-VL-7B and surpasses Qwen3-VL-8B on four of six reported GUI benchmarks, establishing block-wise diffusion as a practical generative paradigm for multimodal GUI agents.
UI-Venus-2 achieves unprecedented environment coverage and task reliability, paving the way for dependable multimodal GUI agents in real-world applications.
Self-evolving LLMs can amplify adversarial threats, making every known attack lineage-persistent and exposing critical vulnerabilities that static defenses can't address.
VISTA achieves a remarkable accuracy increase in GUI grounding tasks by leveraging multiple views, transforming how models learn from visual data.
LLM-powered autonomous agents are alarmingly susceptible to multi-turn, context-aware attacks that bypass standard security measures, nearly doubling the risk trigger rate.
Current mobile GUI agents, despite progress on existing benchmarks, crumble under the realistic demands of user-centric tasks, revealing critical weaknesses in perception, memory, and robustness.
