activity
20232026
most citedMobile-Bench: An Evaluation Benchmark for LLM-based Mobile Agents

1 citations · 2 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

CoME: Empowering Channel-of-Mobile-Experts with Informative Hybrid-Capabilities Reasoning

Yuxuan Liu, Weikai Xu, Kun Huang +9

Mobile Agents can autonomously execute user instructions, which requires hybrid-capabilities reasoning, including screen summary, subtask planning, action decision and action funct…

cs.CL2025

MobileIPL: Enhancing Mobile Agents Thinking Process via Iterative Preference Learning

Kun Huang, Weikai Xu, Yuxuan Liu +6

The Chain of Action-Planning Thoughts (CoaT) paradigm has been shown to improve the reasoning performance of VLM-based mobile agents in GUI tasks. However, the scarcity of diverse…

cs.CL2025

Mobile-Bench-v2: A More Realistic and Comprehensive Benchmark for VLM-based Mobile Agents

Weikai Xu, Zhizheng Jiang, Yuxuan Liu +7

VLM-based mobile agents are increasingly popular due to their capabilities to interact with smartphone GUIs and XML-structured texts and to complete daily tasks. However, existing…

cs.CL2024

MobileVLM: A Vision-Language Model for Better Intra- and Inter-UI Understanding

Qinzhuo Wu, Weikai Xu, Wei Liu +6

Recently, mobile AI agents based on VLMs have been gaining increasing attention. These works typically utilize VLM as a foundation, fine-tuning it with instruction-based mobile dat…

cs.CL2024★ 1 cited

PMSS: Pretrained Matrices Skeleton Selection for LLM Fine-tuning

Qibin Wang, Xiaolin Hu, Weikai Xu +3

Low-rank adaptation (LoRA) and its variants have recently gained much interest due to their ability to avoid excessive inference costs. However, LoRA still encounters the following…