14 citations · 44 across the 16 of their papers we have counts for
16 papers
From Boundaries to Semantics: Prompt-Guided Multi-Task Learning for Petrographic Thin-section Segmentation
Yili Ren, Shiqi Wen, Li Hou +8
Grain-edge segmentation (GES) and lithology semantic segmentation (LSS) are two pivotal tasks for quantifying rock fabric and composition. However, these two tasks are often treate…
CytoCrowd: A Multi-Annotator Benchmark Dataset for Cytology Image Analysis
Yonghao Si, Xingyuan Zeng, Zhao Chen +4
High-quality annotated datasets are crucial for advancing machine learning in medical image analysis. However, a critical gap exists: most datasets either offer a single, clean gro…
SCAR: A Characterization Scheme for Multi-Modal Dataset
Ri Su, Zhao Chen, Caleb Chen Cao +2
Foundation models exhibit remarkable generalization across diverse tasks, largely driven by the characteristics of their training data. Recent data-centric methods like pruning and…
Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network
Tong Li, Jiale Deng, Yanyan Shen +3
Heterogeneous graph neural networks (HGNs) are prominent approaches to node classification tasks on heterogeneous graphs. Despite the superior performance, insights about the predi…
Two-Stage Holistic and Contrastive Explanation of Image Classification
Weiyan Xie, Xiao-Hui Li, Zhi Lin +3
The need to explain the output of a deep neural network classifier is now widely recognized. While previous methods typically explain a single class in the output, we advocate expl…
Model Debiasing via Gradient-based Explanation on Representation
Jindi Zhang, Luning Wang, Dan Su +3
Machine learning systems produce biased results towards certain demographic groups, known as the fairness problem. Recent approaches to tackle this problem learn a latent code (i.e…