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Beyond a Single Judge: The Evidence-Grounded, Social-Weighted Persona Panel for Generative UI Evaluation
Zheng Wu, Yibo Luo, Pu Zhang +2
Generative UI (GenUI) lets large language models synthesize a complete, renderable interface directly from a natural-language instruction, but evaluating the quality of what they g…
Would You Walk to the Car Wash? Salience Bias in LLM Commonsense Reasoning
Zheng Wu, Chenhao Xue, Shijie Zheng +3
Despite advances in complex reasoning, large language models (LLMs) can prioritize explicit input conditions over implicit task prerequisites. In everyday commonsense reasoning, th…
Mobile-Aptus: Confidence-Driven Proactive and Robust Interaction in MLLM-based Mobile-Using Agents
Zheng Wu, Pengzhou Cheng, Zongru Wu +5
Recent advancements in multimodal large language models (MLLMs) have shown exceptional potential in enabling mobile-using agents to autonomously execute human instructions. However…
GUI-CIDER: Mid-training GUI Agents via Causal Internalization and Density-aware Exemplar Reselection
Zheng Wu, Chengcheng Han, Zhengxi Lu +5
Despite the rapid progress of multimodal large language models in building Graphical User Interface (GUI) agents, their real-world task completion is fundamentally bottlenecked by…
MineExplorer: Evaluating Open-World Exploration of MLLM Agents in Minecraft
Tianjie Ju, Yueqing Sun, Zheng Wu +7
Multimodal large language models (MLLMs) have shown strong capabilities in perception, reasoning, and action generation. However, their ability to sustain exploration in dynamic op…
Say One Thing, Do Another? Diagnosing Reasoning-Execution Gaps in VLM-Powered Mobile-Use Agents
Lingzhong Dong, Ziqi Zhou, Shuaibo Yang +6
Mobile-use agents powered by vision-language models (VLMs) have shown great potential in interpreting natural language instructions and generating corresponding actions based on mo…
Quick on the Uptake: Eliciting Implicit Intents from Human Demonstrations for Personalized Mobile-Use Agents
Zheng Wu, Heyuan Huang, Yanjia Yang +6
As multimodal large language models advance rapidly, the automation of mobile tasks has become increasingly feasible through the use of mobile-use agents that mimic human interacti…
Atomic-to-Compositional Generalization for Mobile Agents with A New Benchmark and Scheduling System
Yuan Guo, Tingjia Miao, Zheng Wu +3
Autonomous agents powered by multimodal large language models have been developed to facilitate task execution on mobile devices. However, prior work has predominantly focused on a…
Hidden Ghost Hand: Unveiling Backdoor Vulnerabilities in MLLM-Powered Mobile GUI Agents
Pengzhou Cheng, Haowen Hu, Zheng Wu +4
Graphical user interface (GUI) agents powered by multimodal large language models (MLLMs) have shown greater promise for human-interaction. However, due to the high fine-tuning cos…
Smoothing Grounding and Reasoning for MLLM-Powered GUI Agents with Query-Oriented Pivot Tasks
Zongru Wu, Pengzhou Cheng, Zheng Wu +3
Perception-enhanced pre-training, particularly through grounding techniques, is widely adopted to enhance the performance of graphical user interface (GUI) agents. However, in reso…