1 citations · 1 across the 3 of their papers we have counts for
5 papers
Which Models Work Well Together? Measuring Heterogeneity for LLM Team Selection
Liangyu Teng, Hengsong Liu, Juncen Guo +4
The performance ceiling of an LLM team is constrained not only by individual model capabilities, but also by inter-member error resonance and predictive differences. Although heter…
Robust Embodied Perception in Dynamic Environments via Disentangled Weight Fusion
Juncen Guo, Xiaoguang Zhu, Jingyi Wu +4
Embodied perception systems face severe challenges of dynamic environment distribution drift when they continuously interact in open physical spaces. However, the existing domain i…
OEL-AD: An Online Evolutive Learning Framework for Cross-Region Adaptive Autonomous Driving
Jiayue Jin, Lang Qian, Jingyu Zhang +2
Autonomous driving models have achieved great progress in recent years, yet most existing approaches remain static, following a train-then-deploy paradigm that lacks the ability to…
DSRC: Learning Density-insensitive and Semantic-aware Collaborative Representation against Corruptions
Jingyu Zhang, Yilei Wang, Lang Qian +5
As a potential application of Vehicle-to-Everything (V2X) communication, multi-agent collaborative perception has achieved significant success in 3D object detection. While these m…
Explain EEG-based End-to-end Deep Learning Models in the Frequency Domain
Hanqi Wang, Kun Yang, Jingyu Zhang +2
The recent rise of EEG-based end-to-end deep learning models presents a significant challenge in elucidating how these models process raw EEG signals and generate predictions in th…