most citedBeyond Training: Enabling Self-Evolution of Agents with MOBIMEM

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI20251 cited

Beyond Training: Enabling Self-Evolution of Agents with MOBIMEM

Zibin Liu, Cheng Zhang, Xi Zhao +6

Large Language Model (LLM) agents are increasingly deployed to automate complex workflows in mobile and desktop environments. However, current model-centric agent architectures str…

cs.AR2025

From Principles to Practice: A Systematic Study of LLM Serving on Multi-core NPUs

Tianhao Zhu, Dahu Feng, Erhu Feng +1

With the widespread adoption of Large Language Models (LLMs), the demand for high-performance LLM inference services continues to grow. To meet this demand, a growing number of AI…

cs.MA2025

MobiAgent: A Systematic Framework for Customizable Mobile Agents

Cheng Zhang, Erhu Feng, Xi Zhao +7

With the rapid advancement of Vision-Language Models (VLMs), GUI-based mobile agents have emerged as a key development direction for intelligent mobile systems. However, existing a…

cs.LG2025

Get Experience from Practice: LLM Agents with Record & Replay

Erhu Feng, Wenbo Zhou, Zibin Liu +8

AI agents, empowered by Large Language Models (LLMs) and communication protocols such as MCP and A2A, have rapidly evolved from simple chatbots to autonomous entities capable of ex…

cs.AI2025

AutoEval: A Practical Framework for Autonomous Evaluation of Mobile Agents

Jiahui Sun, Zhichao Hua, Yubin Xia

Comprehensive evaluation of mobile agents can significantly advance their development and real-world applicability. However, existing benchmarks lack practicality and scalability d…