6 citations · 18 across the 29 of their papers we have counts for
32 papers
Xiaomi-TabLDM: A Tabular Foundation Model Technical Report
TabLDM Team, Penghui Wang, Wei Liu +12
We introduce Xiaomi-TabLDM, a tabular large data foundation model for classification and regression via in-context learning, which delivers superior prediction accuracy without req…
Task-Adaptive Rubrics for GUI Reward Modeling
Tao Xiong, Xavier Hu, Wenkai Wang +6
Recent studies on GUI agents have increasingly focused on outcome reward modeling, which assigns outcome rewards by judging whether an executed trajectory satisfies the success cri…
Xiaomi-GUI-0 Technical Report
Wanxia Cao, Chengzhen Duan, Pei Fu +29
Graphical user interface (GUI) agents build on vision-language models to complete user tasks end-to-end in real applications through interface actions such as tapping, swiping, tex…
Scaling Model and Data for Multilingual Machine Translation with Open Large Language Models
Yuzhe Shang, Pengzhi Gao, Wei Liu +2
Open large language models (LLMs) have demonstrated improving multilingual capabilities in recent years. In this paper, we present a study of open LLMs for multilingual machine tra…
MobileBench-OL: A Comprehensive Chinese Benchmark for Evaluating Mobile GUI Agents in Real-World Environment
Qinzhuo Wu, Zhizhuo Yang, Hanhao Li +3
Recent advances in mobile Graphical User Interface (GUI) agents highlight the growing need for comprehensive evaluation benchmarks. While new online benchmarks offer more realistic…
STEP: Success-Rate-Aware Trajectory-Efficient Policy Optimization
Yuhan Chen, Yuxuan Liu, Long Zhang +3
Multi-turn interaction remains challenging for online reinforcement learning. A common solution is trajectory-level optimization, which treats each trajectory as a single training…
VecInfer: Efficient LLM Inference with Low-Bit KV Cache via Outlier-Suppressed Vector Quantization
Dingyu Yao, Chenxu Yang, Zhengyang Tong +4
The Key-Value (KV) cache introduces substantial memory overhead during large language model (LLM) inference. Although existing vector quantization (VQ) methods reduce KV cache usag…
GUI-PRA: Process Reward Agent for GUI Tasks
Tao Xiong, Xavier Hu, Yurun Chen +6
Long-horizon GUI automation remains challenging due to error accumulation over extended interaction sequences. Process Reward Models (PRMs) provide dense step-level supervision for…
Attention Basin: Why Contextual Position Matters in Large Language Models
Zihao Yi, Delong Zeng, Zhenqing Ling +6
The performance of Large Language Models (LLMs) is significantly sensitive to the contextual position of information in the input. To investigate the mechanism behind this position…
Mobile GUI Agents under Real-world Threats: Are We There Yet?
Guohong Liu, Jialei Ye, Jiacheng Liu +5
Recent years have witnessed a rapid development of mobile GUI agents powered by large language models (LLMs), which can autonomously execute diverse device-control tasks based on n…
TaP: A Taxonomy-Guided Framework for Automated and Scalable Preference Data Generation
Renren Jin, Tianhao Shen, Xinwei Wu +9
Conducting supervised and preference fine-tuning of large language models (LLMs) requires high-quality datasets to improve their ability to follow instructions and align with human…
End-to-End Optimization of LLM-Driven Multi-Agent Search Systems via Heterogeneous-Group-Based Reinforcement Learning
Guanzhong Chen, Shaoxiong Yang, Chao Li +3
Large language models (LLMs) are versatile, yet their deployment in complex real-world settings is limited by static knowledge cutoffs and the difficulty of producing controllable…
BacktrackAgent: Enhancing GUI Agent with Error Detection and Backtracking Mechanism
Qinzhuo Wu, Pengzhi Gao, Wei Liu +1
Graphical User Interface (GUI) agents have gained substantial attention due to their impressive capabilities to complete tasks through multiple interactions within GUI environments…
TailorKV: A Hybrid Framework for Long-Context Inference via Tailored KV Cache Optimization
Dingyu Yao, Bowen Shen, Zheng Lin +4
The Key-Value (KV) cache in generative large language models (LLMs) introduces substantial memory overhead. Existing works mitigate this burden by offloading or compressing the KV…
GUI-Shift: Enhancing VLM-Based GUI Agents through Self-supervised Reinforcement Learning
Longxi Gao, Li Zhang, Pengzhi Gao +3
Training effective Vision-Language Models (VLMs) for GUI agents typically depends on large-scale annotated datasets, whose collection is both labor-intensive and error-prone. We in…
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…
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…
MobileSteward: Integrating Multiple App-Oriented Agents with Self-Evolution to Automate Cross-App Instructions
Yuxuan Liu, Hongda Sun, Wei Liu +3
Mobile phone agents can assist people in automating daily tasks on their phones, which have emerged as a pivotal research spotlight. However, existing procedure-oriented agents str…
ReachAgent: Enhancing Mobile Agent via Page Reaching and Operation
Qinzhuo Wu, Wei Liu, Jian Luan +1
Recently, mobile AI agents have gained increasing attention. Given a task, mobile AI agents can interact with mobile devices in multiple steps and finally form a GUI flow that solv…
DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models
Xiaolin Hu, Xiang Cheng, Peiyu Liu +4
Low-rank adaptation (LoRA) reduces the computational and memory demands of fine-tuning large language models (LLMs) by approximating updates with low-rank matrices. However, low-ra…
KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models
Weijie Chen, Ting Bai, Jinbo Su +3
Large language models with retrieval-augmented generation encounter a pivotal challenge in intricate retrieval tasks, e.g., multi-hop question answering, which requires the model t…
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…
HoPE: A Novel Positional Encoding Without Long-Term Decay for Enhanced Context Awareness and Extrapolation
Yuhan Chen, Ang Lv, Jian Luan +2
Many positional encodings (PEs) are designed to exhibit long-term decay, based on an entrenched and long-standing inductive opinion: tokens farther away from the current position c…
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…