34 citations · 93 across the 7 of their papers we have counts for
7 papers
Interactive Editing for Text Summarization
Yujia Xie, Xun Wang, Si-Qing Chen +2
Summarizing lengthy documents is a common and essential task in our daily lives. Although recent advancements in neural summarization models can assist in crafting general-purpose…
An Evaluation on Large Language Model Outputs: Discourse and Memorization
Adrian de Wynter, Xun Wang, Alex Sokolov +2
We present an empirical evaluation of various outputs generated by nine of the most widely-available large language models (LLMs). Our analysis is done with off-the-shelf, readily-…
Pay Attention to Your Tone: Introducing a New Dataset for Polite Language Rewrite
Xun Wang, Tao Ge, Allen Mao +3
We introduce \textsc{PoliteRewrite} -- a dataset for polite language rewrite which is a novel sentence rewrite task. Compared with previous text style transfer tasks that can be mo…
Latent Prompt Tuning for Text Summarization
Yubo Zhang, Xingxing Zhang, Xun Wang +2
Prompts with different control signals (e.g., length, keywords, etc.) can be used to control text summarization. When control signals are available, they can control the properties…
Momentum Calibration for Text Generation
Xingxing Zhang, Yiran Liu, Xun Wang +5
The input and output of most text generation tasks can be transformed to two sequences of tokens and they can be modeled using sequence-to-sequence learning modeling tools such as…
MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low Resource Machine Translation
Rumeng Li, Xun Wang, Hong Yu
Manipulating training data leads to robust neural models for MT.
Reading Comprehension using Entity-based Memory Network
Xun Wang, Katsuhito Sudoh, Masaaki Nagata +3
This paper introduces a novel neural network model for question answering, the \emph{entity-based memory network}. It enhances neural networks' ability of representing and calculat…