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most citedRAEE: A Robust Retrieval-Augmented Early Exit Framework for Efficient Inference

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cs.CV2025

AD-EE: Early Exiting for Fast and Reliable Vision-Language Models in Autonomous Driving

Lianming Huang, Haibo Hu, Yufei Cui +4

With the rapid advancement of autonomous driving, deploying Vision-Language Models (VLMs) to enhance perception and decision-making has become increasingly common. However, the rea…

cs.CV2025

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning

Jiacheng Zuo, Haibo Hu, Zikang Zhou +6

In the pursuit of robust autonomous driving systems, models trained on real-world datasets often struggle to adapt to new environments, particularly when confronted with corner cas…

cs.CV2025

Advancing Multiple Instance Learning with Continual Learning for Whole Slide Imaging

Xianrui Li, Yufei Cui, Jun Li +1

Advances in medical imaging and deep learning have propelled progress in whole slide image (WSI) analysis, with multiple instance learning (MIL) showing promise for efficient and a…

cs.CV2024

GeneQuery: A General QA-based Framework for Spatial Gene Expression Predictions from Histology Images

Ying Xiong, Linjing Liu, Yufei Cui +4

Gene expression profiling provides profound insights into molecular mechanisms, but its time-consuming and costly nature often presents significant challenges. In contrast, whole-s…

cs.CV2024

BAHOP: Similarity-based Basin Hopping for A fast hyper-parameter search in WSI classification

Jun Wang, Yu Mao, Yufei Cui +2

Pre-processing whole slide images (WSIs) can impact classification performance. Our study shows that using fixed hyper-parameters for pre-processing out-of-domain WSIs can signific…

cs.CV2024

IHC Matters: Incorporating IHC analysis to H&E Whole Slide Image Analysis for Improved Cancer Grading via Two-stage Multimodal Bilinear Pooling Fusion

Jun Wang, Yu Mao, Yufei Cui +2

Immunohistochemistry (IHC) plays a crucial role in pathology as it detects the over-expression of protein in tissue samples. However, there are still fewer machine learning model s…