Potential and Limitations of LLMs in Capturing Structured Semantics: A Case Study on SRL

no code implementations • 10 May 2024 • Ning Cheng, Zhaohui Yan, ZiMing Wang, Zhijie Li, Jiaming Yu, Zilong Zheng, Kewei Tu, Jinan Xu, Wenjuan Han

Large Language Models (LLMs) play a crucial role in capturing structured semantics to enhance language understanding, improve interpretability, and reduce bias.

CausalCellSegmenter: Causal Inference inspired Diversified Aggregation Convolution for Pathology Image Segmentation

no code implementations • 10 Mar 2024 • Dawei Fan, Yifan Gao, Jiaming Yu, Yanping Chen, Wencheng Li, Chuancong Lin, Kaibin Li, Changcai Yang, Riqing Chen, Lifang Wei

Deep learning models have shown promising performance for cell nucleus segmentation in the field of pathology image analysis.

Causal Inference Image Segmentation +1

OpenNDD: Open Set Recognition for Neurodevelopmental Disorders Detection

no code implementations • 28 Jun 2023 • Jiaming Yu, Zihao Guan, Xinyue Chang, Shujie Liu, Zhenshan Shi, Xiumei Liu, Changcai Yang, Riqing Chen, Lanyan Xue, Lifang Wei

Since the strong comorbid similarity in NDDs, such as attention-deficit hyperactivity disorder, can interfere with the accurate diagnosis of autism spectrum disorder (ASD), identifying unknown classes is extremely crucial and challenging from NDDs.

open-set classification Open Set Learning