2 citations · 3 across the 5 of their papers we have counts for
6 papers
What Makes High-Magnification Knowledge Transferable? A Study of Cross-Resolution Distillation in Whole-Slide Imaging
Zhiyuan Yang, Jiahao Cheng, Mahdi S. Hosseini
Cross-resolution knowledge distillation aims to improve low-magnification whole- slide analysis by transferring high-magnification representations, yet the conditions for useful tr…
Gated Spatial Redundancy Projection for Pathology Transformer Attentions
Zhiyuan Yang, Jiahao Cheng, Vincent Quoc-Huy Trinh +1
Transformer models are increasingly used for whole-slide image analysis in computational pathology. Yet, WSIs differ fundamentally from natural images: neighbouring patches often c…
Simple Token-Efficient Vision-Language Model for Case-level Pathology Synoptic Report Generation
Zhiyuan Yang, Jiahao Cheng, Vincent Quoc-Huy Trinh +1
Generating clinically useful pathology reports for pathology cases from whole-slide images (WSIs) is challenging due to gigapixel resolution, long visual-token sequences, and the c…
SD4R: Sparse-to-Dense Learning for 3D Object Detection with 4D Radar
Xiaokai Bai, Jiahao Cheng, Songkai Wang +5
4D radar measurements offer an affordable and weather-robust solution for 3D perception. However, the inherent sparsity and noise of radar point clouds present significant challeng…
Chain-of-Thought Prompting Obscures Hallucination Cues in Large Language Models: An Empirical Evaluation
Jiahao Cheng, Tiancheng Su, Jia Yuan +5
Large Language Models (LLMs) often exhibit \textit{hallucinations}, generating factually incorrect or semantically irrelevant content in response to prompts. Chain-of-Thought (CoT)…
Self-supervised feature distillation and design of experiments for efficient training of micromechanical deep learning surrogates
Patxi Fernandez-Zelaia, Jason Mayeur, Jiahao Cheng +3
Machine learning surrogate emulators are needed in engineering design and optimization tasks to rapidly emulate computationally expensive physics-based models. In micromechanics pr…