11 citations · 13 across the 9 of their papers we have counts for
4 papers · 1 filter
ITPNet: Towards Instantaneous Trajectory Prediction for Autonomous Driving
Rongqing Li, Changsheng Li, Yuhang Li +5
Trajectory prediction of agents is crucial for the safety of autonomous vehicles, whereas previous approaches usually rely on sufficiently long-observed trajectory to predict the f…
DREAM: Domain-agnostic Reverse Engineering Attributes of Black-box Model
Rongqing Li, Jiaqi Yu, Changsheng Li +3
Deep learning models are usually black boxes when deployed on machine learning platforms. Prior works have shown that the attributes (e.g., the number of convolutional layers) of a…
Fira: Can We Achieve Full-rank Training of LLMs Under Low-rank Constraint?
Xi Chen, Kaituo Feng, Changsheng Li +4
Low-rank training has emerged as a promising approach for reducing memory usage in training Large Language Models (LLMs). Previous methods either rely on decomposing weight matrice…
On the Road to Portability: Compressing End-to-End Motion Planner for Autonomous Driving
Kaituo Feng, Changsheng Li, Dongchun Ren +2
End-to-end motion planning models equipped with deep neural networks have shown great potential for enabling full autonomous driving. However, the oversized neural networks render…