2 citations · 5 across the 7 of their papers we have counts for
7 papers
LLM-Generated Natural Language Meets Scaling Laws: New Explorations and Data Augmentation Methods
Zhenhua Wang, Guang Xu, Ming Ren
With the ascent of large language models (LLM), natural language processing has witnessed enhancements, such as LLM-based data augmentation. Nonetheless, prior research harbors two…
Exploring the law of text geographic information
Zhenhua Wang, Daiyu Zhang, Ming Ren +1
Textual geographic information is indispensable and heavily relied upon in practical applications. The absence of clear distribution poses challenges in effectively harnessing geog…
Will sentiment analysis need subculture? A new data augmentation approach
Zhenhua Wang, Simin He, Guang Xu +1
Nowadays, the omnipresence of the Internet has fostered a subculture that congregates around the contemporary milieu. The subculture artfully articulates the intricacies of human f…
Yes, DLGM! A novel hierarchical model for hazard classification
Zhenhua Wang, Ming Ren, Dong Gao +1
Hazards can be exposed by HAZOP as text information, and studying their classification is of great significance to the development of industrial informatics, which is conducive to…
A new hazard event classification model via deep learning and multifractal
Zhenhua Wang, Bin Wang, Ming Ren +1
Hazard and operability analysis (HAZOP) is the paradigm of industrial safety that can reveal the hazards of process from its node deviations, consequences, causes, measures and sug…
A Zipf's Law-based Text Generation Approach for Addressing Imbalance in Entity Extraction
Zhenhua Wang, Ming Ren, Dong Gao +1
Entity extraction is critical in the intelligent advancement across diverse domains. Nevertheless, a challenge to its effectiveness arises from the data imbalance. This paper propo…
A New Multifractal-based Deep Learning Model for Text Mining
Zhenhua Wang, Ming Ren, Dong Gao
In this world full of uncertainty, where the fabric of existence weaves patterns of complexity, multifractal emerges as beacons of insight, illuminating them. As we delve into the…