2 citations · 2 across the 8 of their papers we have counts for
8 papers
Skill Training with Corruption and Reconstruction Loop
Mo Li, Zixin Yin, Ting Cao +3
Large Language Models (LLMs) often struggle in highly specialized domains. Rather than parameter-level adaptation of LLMs which is costly and difficult to interpret, external skill…
Sparse Compositional Flow Matching by geometric assembly from motion primitives
Yan Tang, Yuanbo Tang, Tingyu Cao +2
Embodied trajectories, such as the executable motion sequences of robotic manipulators, underwater vehicles, and mobile robots, are a fundamental output of embodied AI. Modern gene…
ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration
Gaole Dai, Shiqi Jiang, Ting Cao +5
Reward is critical to the evaluation and training of large language models (LLMs). However, existing rule-based or model-based reward methods struggle to generalize to GUI agents,…
Zoomer: Adaptive Image Focus Optimization for Black-box MLLM
Jiaxu Qian, Chendong Wang, Yifan Yang +16
Multimodal large language models (MLLMs) such as GPT-4o, Gemini Pro, and Claude 3.5 have enabled unified reasoning over text and visual inputs, yet they often hallucinate in real w…
Advancing Mobile GUI Agents: A Verifier-Driven Approach to Practical Deployment
Gaole Dai, Shiqi Jiang, Ting Cao +5
We propose V-Droid, a mobile GUI task automation agent. Unlike previous mobile agents that utilize Large Language Models (LLMs) as generators to directly generate actions at each s…
Babel: A Scalable Pre-trained Model for Multi-Modal Sensing via Expandable Modality Alignment
Shenghong Dai, Shiqi Jiang, Yifan Yang +4
This paper presents Babel, the expandable modality alignment model, specially designed for multi-modal sensing. While there has been considerable work on multi-modality alignment,…
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…
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…