5 papers
A Scene-aware Models Adaptation Scheme for Cross-scene Online Inference on Mobile Devices
Yunzhe Li, Hongzi Zhu, Zhuohong Deng +5
Emerging Artificial Intelligence of Things (AIoT) applications desire online prediction using deep neural network (DNN) models on mobile devices. However, due to the movement of de…
Adacc: An Adaptive Framework Unifying Compression and Activation Recomputation for LLM Training
Ping Chen, Zhuohong Deng, Ping Li +6
Training large language models (LLMs) is often constrained by GPU memory limitations. To alleviate memory pressure, activation recomputation and data compression have been proposed…
Saga: Capturing Multi-granularity Semantics from Massive Unlabelled IMU Data for User Perception
Yunzhe Li, Facheng Hu, Hongzi Zhu +4
Inertial measurement units (IMUs), have been prevalently used in a wide range of mobile perception applications such as activity recognition and user authentication, where a large…
Prism: Mining Task-aware Domains in Non-i.i.d. IMU Data for Flexible User Perception
Yunzhe Li, Facheng Hu, Hongzi Zhu +5
A wide range of user perception applications leverage inertial measurement unit (IMU) data for online prediction. However, restricted by the non-i.i.d. nature of IMU data collected…
SimGen: Simulator-conditioned Driving Scene Generation
Yunsong Zhou, Michael Simon, Zhenghao Peng +4
Controllable synthetic data generation can substantially lower the annotation cost of training data. Prior works use diffusion models to generate driving images conditioned on the…