5 citations · 11 across the 7 of their papers we have counts for
5 papers · 1 filter
VTechAGP: An Academic-to-General-Audience Text Paraphrase Dataset and Benchmark Models
Ming Cheng, Jiaying Gong, Chenhan Yuan +3
Existing text simplification or paraphrase datasets mainly focus on sentence-level text generation in a general domain. These datasets are typically developed without using domain…
Zero-shot Temporal Relation Extraction with ChatGPT
Chenhan Yuan, Qianqian Xie, Sophia Ananiadou
The goal of temporal relation extraction is to infer the temporal relation between two events in the document. Supervised models are dominant in this task. In this work, we investi…
Clustering-based Unsupervised Generative Relation Extraction
Chenhan Yuan, Ryan Rossi, Andrew Katz +1
This paper focuses on the problem of unsupervised relation extraction. Existing probabilistic generative model-based relation extraction methods work by extracting sentence feature…
Efficient text generation of user-defined topic using generative adversarial networks
Chenhan Yuan, Yi-chin Huang, Cheng-Hung Tsai
This study focused on efficient text generation using generative adversarial networks (GAN). Assuming that the goal is to generate a paragraph of a user-defined topic and sentiment…
Personalized sentence generation using generative adversarial networks with author-specific word usage
Chenhan Yuan, Yi-Chin Huang
The author-specific word usage is a vital feature to let readers perceive the writing style of the author. In this work, a personalized sentence generation method based on generati…