6 citations · 10 across the 24 of their papers we have counts for
11 papers · 1 filter
ColorEcosystem: Powering Personalized, Standardized, and Trustworthy Agentic Service in massive-agent Ecosystem
Fangwen Wu, Zheng Wu, Jihong Wang +11
With the rapid development of (multimodal) large language model-based agents, the landscape of agentic service management has evolved from single-agent systems to multi-agent syste…
ColorAgent: Building A Robust, Personalized, and Interactive OS Agent
Ning Li, Qiqiang Lin, Zheng Wu +19
With the advancements in hardware, software, and large language model technologies, the interaction between humans and operating systems has evolved from the command-line interface…
ColorBench: Benchmarking Mobile Agents with Graph-Structured Framework for Complex Long-Horizon Tasks
Yuanyi Song, Heyuan Huang, Qiqiang Lin +9
The rapid advancement of multimodal large language models has enabled agents to operate mobile devices by directly interacting with graphical user interfaces, opening new possibili…
HatLLM: Hierarchical Attention Masking for Enhanced Collaborative Modeling in LLM-based Recommendation
Yu Cui, Feng Liu, Jiawei Chen +6
Recent years have witnessed a surge of research on leveraging large language models (LLMs) for sequential recommendation. LLMs have demonstrated remarkable potential in inferring u…
VeriOS: Query-Driven Proactive Human-Agent-GUI Interaction for Trustworthy OS Agents
Zheng Wu, Heyuan Huang, Xingyu Lou +8
With the rapid progress of multimodal large language models, operating system (OS) agents become increasingly capable of automating tasks through on-device graphical user interface…
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…
MobileUse: A GUI Agent with Hierarchical Reflection for Autonomous Mobile Operation
Ning Li, Xiangmou Qu, Jiamu Zhou +6
Recent advances in Multimodal Large Language Models (MLLMs) have enabled the development of mobile agents that can understand visual inputs and follow user instructions, unlocking…
OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation
Shengjia Zhang, Junjie Wu, Jiawei Chen +7
Human cognition operates through two complementary modes: fast intuitive thinking and slow deliberate thinking. Vanilla large language models (LLMs) predominantly follow the fast-t…
Field Matters: A Lightweight LLM-enhanced Method for CTR Prediction
Yu Cui, Feng Liu, Jiawei Chen +6
Click-through rate (CTR) prediction is a fundamental task in modern recommender systems. In recent years, the integration of large language models (LLMs) has been shown to effectiv…
MSL: Not All Tokens Are What You Need for Tuning LLM as a Recommender
Bohao Wang, Feng Liu, Jiawei Chen +7
Large language models (LLMs), known for their comprehension capabilities and extensive knowledge, have been increasingly applied to recommendation systems (RS). Given the fundament…
TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation
Jiaqing Zhang, Mingjia Yin, Hao Wang +5
In the era of data-centric AI, the focus of recommender systems has shifted from model-centric innovations to data-centric approaches. The success of modern AI models is built on l…