5 papers
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…
Caution for the Environment: Multimodal LLM Agents are Susceptible to Environmental Distractions
Xinbei Ma, Yiting Wang, Yao Yao +4
This paper investigates the faithfulness of multimodal large language model (MLLM) agents in a graphical user interface (GUI) environment, aiming to address the research question o…
OS-Kairos: Adaptive Interaction for MLLM-Powered GUI Agents
Pengzhou Cheng, Zheng Wu, Zongru Wu +3
Autonomous graphical user interface (GUI) agents powered by multimodal large language models have shown great promise. However, a critical yet underexplored issue persists: over-ex…
Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study
Menglong Cui, Pengzhi Gao, Wei Liu +2
Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…
In-Context Learning with Iterative Demonstration Selection
Chengwei Qin, Aston Zhang, Chen Chen +2
Spurred by advancements in scale, large language models (LLMs) have demonstrated strong few-shot learning ability via in-context learning (ICL). However, the performance of ICL has…