activity
20212026
most citedAutoDroid: LLM-powered Task Automation in Android

12 citations · 17 across the 14 of their papers we have counts for

collaborators

15 papers

cs.RO2026

Embodied.cpp: A Portable Inference Runtime of Embodied AI Models on Heterogeneous Robots

Ling Xu, Borui Li, Hao Wu +8

Embodied AI models now span vision-language-action (VLA) models and world-action models (WAMs), but practical deployment remains fragmented across model-specific Python stacks, bac…

cs.RO2026

MemCompiler: Compile, Don't Inject -- State-Conditioned Memory for Embodied Agents

Xin Ding, Xinrui Wang, Yifan Yang +9

Existing memory systems for embodied agents typically inject retrieved memory as static context at episode start, a paradigm we term Ahead-of-time Monolithic Memory Injection (AMMI…

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.CV2026

Em-Garde: A Propose-Match Framework for Proactive Streaming Video Understanding

Yikai Zheng, Xin Ding, Yifan Yang +6

Recent advances in Streaming Video Understanding has enabled a new interaction paradigm where models respond proactively to user queries. Current proactive VideoLLMs rely on per-fr…

cs.RO2025

AdaNav: Adaptive Reasoning with Uncertainty for Vision-Language Navigation

Xin Ding, Jianyu Wei, Yifan Yang +10

Vision Language Navigation (VLN) requires agents to follow natural language instructions by grounding them in sequential visual observations over long horizons. Explicit reasoning…

cs.DC2025

Scaling LLM Test-Time Compute with Mobile NPU on Smartphones

Zixu Hao, Jianyu Wei, Tuowei Wang +5

Deploying Large Language Models (LLMs) on mobile devices faces the challenge of insufficient performance in smaller models and excessive resource consumption in larger ones. This p…

cs.LG2025

Scaling Up On-Device LLMs via Active-Weight Swapping Between DRAM and Flash

Fucheng Jia, Zewen Wu, Shiqi Jiang +7

Large language models (LLMs) are increasingly being deployed on mobile devices, but the limited DRAM capacity constrains the deployable model size. This paper introduces ActiveFlow…

cs.CV2025

StreamMind: Unlocking Full Frame Rate Streaming Video Dialogue through Event-Gated Cognition

Xin Ding, Hao Wu, Yifan Yang +4

With the rise of real-world human-AI interaction applications, such as AI assistants, the need for Streaming Video Dialogue is critical. To address this need, we introduce StreamMi…

cs.CV2024

Making Every Frame Matter: Continuous Activity Recognition in Streaming Video via Adaptive Video Context Modeling

Hao Wu, Donglin Bai, Shiqi Jiang +6

Video activity recognition has become increasingly important in robots and embodied AI. Recognizing continuous video activities poses considerable challenges due to the fast expans…

cs.LG2024★ 2 cited

Anatomizing Deep Learning Inference in Web Browsers

Qipeng Wang, Shiqi Jiang, Zhenpeng Chen +6

Web applications have increasingly adopted Deep Learning (DL) through in-browser inference, wherein DL inference performs directly within Web browsers. The actual performance of in…

cs.AI2023

Empowering In-Browser Deep Learning Inference on Edge Devices with Just-in-Time Kernel Optimizations

Fucheng Jia, Shiqi Jiang, Ting Cao +9

Web is increasingly becoming the primary platform to deliver AI services onto edge devices, making in-browser deep learning (DL) inference more prominent. Nevertheless, the heterog…

cs.AI2023★ 12 cited

AutoDroid: LLM-powered Task Automation in Android

Hao Wen, Yuanchun Li, Guohong Liu +7

Mobile task automation is an attractive technique that aims to enable voice-based hands-free user interaction with smartphones. However, existing approaches suffer from poor scalab…

cs.LG2023★ 2 cited

AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments

Hao Wen, Yuanchun Li, Zunshuai Zhang +5

Deep learning models are increasingly deployed to edge devices for real-time applications. To ensure stable service quality across diverse edge environments, it is highly desirable…

cs.CV2022★ 1 cited

Turbo: Opportunistic Enhancement for Edge Video Analytics

Yan Lu, Shiqi Jiang, Ting Cao +1

Edge computing is being widely used for video analytics. To alleviate the inherent tension between accuracy and cost, various video analytics pipelines have been proposed to optimi…

cs.CV2021

Multi-modal application: Image Memes Generation

Zhiyuan Liu, Chuanzheng Sun, Yuxin Jiang +2

Meme is an interesting word. Internet memes offer unique insights into the changes in our perception of the world, the media and our own lives. If you surf the Internet for long en…