6 citations · 14 across the 26 of their papers we have counts for
10 papers · 1 filter
Autoware.Flex: Human-Instructed Dynamically Reconfigurable Autonomous Driving Systems
Ziwei Song, Mingsong Lv, Tianchi Ren +3
Existing Autonomous Driving Systems (ADS) independently make driving decisions, but they face two significant limitations. First, in complex scenarios, ADS may misinterpret the env…
SHAP-CAT: A interpretable multi-modal framework enhancing WSI classification via virtual staining and shapley-value-based multimodal fusion
Jun Wang, Yu Mao, Nan Guan +1
The multimodal model has demonstrated promise in histopathology. However, most multimodal models are based on H\&E and genomics, adopting increasingly complex yet black-box designs…
Advances in Multiple Instance Learning for Whole Slide Image Analysis: Techniques, Challenges, and Future Directions
Jun Wang, Yu Mao, Nan Guan +1
Whole slide images (WSIs) are gigapixel-scale digital images of H\&E-stained tissue samples widely used in pathology. The substantial size and complexity of WSIs pose unique analyt…
Retrieval-Augmented Generation for Natural Language Processing: A Survey
Shangyu Wu, Ying Xiong, Yufei Cui +8
Large language models (LLMs) have achieved strong empirical performance in various fields, benefiting from their huge amount of parameters that store knowledge. However, LLMs still…
Grade Like a Human: Rethinking Automated Assessment with Large Language Models
Wenjing Xie, Juxin Niu, Chun Jason Xue +1
While large language models (LLMs) have been used for automated grading, they have not yet achieved the same level of performance as humans, especially when it comes to grading com…
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…
BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction
Zikang Zhou, Haibo Hu, Xinhong Chen +6
Simulating realistic behaviors of traffic agents is pivotal for efficiently validating the safety of autonomous driving systems. Existing data-driven simulators primarily use an en…
RAEE: A Robust Retrieval-Augmented Early Exit Framework for Efficient Inference
Lianming Huang, Shangyu Wu, Yufei Cui +6
Deploying large language model inference remains challenging due to their high computational overhead. Early exit optimizes model inference by adaptively reducing the number of inf…
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…
On the Compressibility of Quantized Large Language Models
Yu Mao, Weilan Wang, Hongchao Du +2
Deploying Large Language Models (LLMs) on edge or mobile devices offers significant benefits, such as enhanced data privacy and real-time processing capabilities. However, it also…