6 papers
MobiFlow: Real-World Mobile Agent Benchmarking through Trajectory Fusion
Yunfei Feng, Xi Zhao, Cheng Zhang +5
Mobile agents can autonomously complete user-assigned tasks through GUI interactions. However, existing mainstream evaluation benchmarks, such as AndroidWorld, operate by connectin…
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…
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…
Characterizing Mobile SoC for Accelerating Heterogeneous LLM Inference
Le Chen, Dahu Feng, Erhu Feng +5
With the rapid advancement of artificial intelligence technologies such as ChatGPT, AI agents, and video generation, contemporary mobile systems have begun integrating these AI cap…
Topology-Aware Virtualization over Inter-Core Connected Neural Processing Units
Dahu Feng, Erhu Feng, Dong Du +4
With the rapid development of artificial intelligence (AI) applications, an emerging class of AI accelerators, termed Inter-core Connected Neural Processing Units (NPU), has been a…
Profiling Apple Silicon Performance for ML Training
Dahua Feng, Zhiming Xu, Rongxiang Wang +1
Apple Silicon has attracted much attention for its performance and role in machine learning (ML) training. Unlike NVIDIA GPUs, which have traditionally dominated ML training, Apple…