18 citations · 27 across the 6 of their papers we have counts for
6 papers
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
Wenwen Yu, Chengquan Zhang, Haoyu Cao +24
Structured text extraction is one of the most valuable and challenging application directions in the field of Document AI. However, the scenarios of past benchmarks are limited, an…
OpenMix: Exploring Outlier Samples for Misclassification Detection
Fei Zhu, Zhen Cheng, Xu-Yao Zhang +1
Reliable confidence estimation for deep neural classifiers is a challenging yet fundamental requirement in high-stakes applications. Unfortunately, modern deep neural networks are…
Rethinking Confidence Calibration for Failure Prediction
Fei Zhu, Zhen Cheng, Xu-Yao Zhang +1
Reliable confidence estimation for the predictions is important in many safety-critical applications. However, modern deep neural networks are often overconfident for their incorre…
Average of Pruning: Improving Performance and Stability of Out-of-Distribution Detection
Zhen Cheng, Fei Zhu, Xu-Yao Zhang +1
Detecting Out-of-distribution (OOD) inputs have been a critical issue for neural networks in the open world. However, the unstable behavior of OOD detection along the optimization…
A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram
Ming-Liang Zhang, Fei Yin, Cheng-Lin Liu
Geometry problem solving (GPS) is a high-level mathematical reasoning requiring the capacities of multi-modal fusion and geometric knowledge application. Recently, neural solvers h…
Robust Metric Learning by Smooth Optimization
Kaizhu Huang, Rong Jin, Zenglin Xu +1
Most existing distance metric learning methods assume perfect side information that is usually given in pairwise or triplet constraints. Instead, in many real-world applications, t…