17 citations · 27 across the 6 of their papers we have counts for
7 papers
Background Invariance Testing According to Semantic Proximity
Zukang Liao, Min Chen
In many applications, machine-learned (ML) models are required to hold some invariance qualities, such as rotation, size, and intensity invariance. Among these, testing for backgro…
MME-CRS: Multi-Metric Evaluation Based on Correlation Re-Scaling for Evaluating Open-Domain Dialogue
Pengfei Zhang, Xiaohui Hu, Kaidong Yu +4
Automatic open-domain dialogue evaluation is a crucial component of dialogue systems. Recently, learning-based evaluation metrics have achieved state-of-the-art performance in open…
Adaptive Prompt Learning-based Few-Shot Sentiment Analysis
Pengfei Zhang, Tingting Chai, Yongdong Xu
In the field of natural language processing, sentiment analysis via deep learning has a excellent performance by using large labeled datasets. Meanwhile, labeled data are insuffici…
CLMB: deep contrastive learning for robust metagenomic binning
Pengfei Zhang, Zhengyuan Jiang, Yixuan Wang +1
The reconstruction of microbial genomes from large metagenomic datasets is a critical procedure for finding uncultivated microbial populations and defining their microbial function…
ML4ML: Automated Invariance Testing for Machine Learning Models
Zukang Liao, Pengfei Zhang, Min Chen
In machine learning (ML) workflows, determining the invariance qualities of an ML model is a common testing procedure. Traditionally, invariance qualities are evaluated using simpl…
Face.evoLVe: A High-Performance Face Recognition Library
Qingzhong Wang, Pengfei Zhang, Haoyi Xiong +1
In this paper, we develop face.evoLVe -- a comprehensive library that collects and implements a wide range of popular deep learning-based methods for face recognition. First of all…
A Sequential Modelling Approach for Indoor Temperature Prediction and Heating Control in Smart Buildings
Yongchao Huang, Hugh Miles, Pengfei Zhang
The rising availability of large volume data, along with increasing computing power, has enabled a wide application of statistical Machine Learning (ML) algorithms in the domains o…