activity
20242026
collaborators

7 papers

cs.AI2026

SmartRAG: Native Graph-Based RAG for Mobile Device

Zhihan Jiang, Meng Li, Shenghao Liu +6

Deploying large language models (LLMs) as personal assistants on mobile devices demands privacy, low latency, and offline availability, yet the computational cost of giant models c…

cs.DC2026

Scalable LLM Agent Tool Access in the Cloud

Mingxin Li, Enge Song, Yueshang Zuo +27

LLM agents increasingly rely on tool calling to act on external systems, and the Model Context Protocol (MCP) has quickly become its de facto interface. Operating MCP at cloud scal…

cs.AI2026

EmbodiSkill: Skill-Aware Reflection for Self-Evolving Embodied Agents

Ruofei Ju, Xinrui Wang, Xin Ding +12

Embodied agents can benefit from skills that guide object search, action execution, and state changes across diverse environments. Since embodied environments vary across layouts,…

cs.DC2026

Efficient Remote KV Cache Reuse with GPU-native Video Codec

Liang Mi, Weijun Wang, Jinghan Chen +3

Remote KV cache reuse fetches KV cache for identical contexts from remote storage, avoiding recomputation, accelerating LLM inference. While it excels in high-speed networks, its p…

cs.AI2025

SMoE: An Algorithm-System Co-Design for Pushing MoE to the Edge via Expert Substitution

Guoying Zhu, Meng Li, Haipeng Dai +6

The Mixture of Experts (MoE) architecture has emerged as a key technique for scaling Large Language Models by activating only a subset of experts per query. Deploying MoE on consum…

cs.CV2024

Empower Vision Applications with LoRA LMM

Liang Mi, Weijun Wang, Wenming Tu +10

Large Multimodal Models (LMMs) have shown significant progress in various complex vision tasks with the solid linguistic and reasoning capacity inherited from large language models…