1 citations · 1 across the 12 of their papers we have counts for
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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…
Sharpen the Spec, Cut the Code: A Case for Generative File System with SYSSPEC
Qingyuan Liu, Mo Zou, Hengbin Zhang +3
File systems are critical OS components that require constant evolution to support new hardware and emerging application needs. However, the traditional paradigm of developing feat…
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…
History Rhymes: Accelerating LLM Reinforcement Learning with RhymeRL
Jingkai He, Tianjian Li, Erhu Feng +5
With the rapid advancement of large language models (LLMs), reinforcement learning (RL) has emerged as a pivotal methodology for enhancing the reasoning capabilities of LLMs. Unlik…
Leveraging OS-Level Primitives for Robotic Action Management
Wenxin Zheng, Boyang Li, Bin Xu +3
End-to-end imitation learning frameworks (e.g., VLA) are increasingly prominent in robotics, as they enable rapid task transfer by learning directly from perception to control, eli…
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…
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…
CHIME: A Case for Efficient Long-Context Attention-FC Disaggregated Inference with DIMM-PIM
Qingyuan Liu, Liyan Chen, Haocheng Wang +6
Attention-FC Disaggregated (AFD) LLM inference systems offload memory-bound Attention operations to memory-rich accelerators (e.g., CPUs, HBM-PIM) while retaining compute-bound Ful…
HeteroPod: XPU-Accelerated Infrastructure Offloading for Commodity Cloud-Native Applications
Bicheng Yang, Jingkai He, Dong Du +2
Cloud-native systems increasingly rely on infrastructure services (e.g., service meshes, monitoring agents), which compete for resources with user applications, degrading performan…
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…