1 citations · 2 across the 6 of their papers we have counts for
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…
Systematic Exploration of Multi-core Architectures for Efficient LLM Serving using WaferAI-SIM
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. Multi-core AI accelerators, such as Groq, Gr…
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…
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…