A survey of natural language generation
This article offers a comprehensive review of the research on Natural Language Generation
(NLG) over the past two decades, especially in relation to data-to-text generation and text-to …
(NLG) over the past two decades, especially in relation to data-to-text generation and text-to …
Text style transfer: A review and experimental evaluation
The stylistic properties of text have intrigued computational linguistics researchers in recent
years. Specifically, researchers have investigated the text style transfer task (TST), which …
years. Specifically, researchers have investigated the text style transfer task (TST), which …
Rlprompt: Optimizing discrete text prompts with reinforcement learning
Prompting has shown impressive success in enabling large pretrained language models
(LMs) to perform diverse NLP tasks, especially when only few downstream data are …
(LMs) to perform diverse NLP tasks, especially when only few downstream data are …
Deep learning for text style transfer: A survey
Text style transfer is an important task in natural language generation, which aims to control
certain attributes in the generated text, such as politeness, emotion, humor, and many …
certain attributes in the generated text, such as politeness, emotion, humor, and many …
Reformulating unsupervised style transfer as paraphrase generation
Modern NLP defines the task of style transfer as modifying the style of a given sentence
without appreciably changing its semantics, which implies that the outputs of style transfer …
without appreciably changing its semantics, which implies that the outputs of style transfer …
A recipe for arbitrary text style transfer with large language models
In this paper, we leverage large language models (LMs) to perform zero-shot text style
transfer. We present a prompting method that we call augmented zero-shot learning, which …
transfer. We present a prompting method that we call augmented zero-shot learning, which …
CommonGen: A constrained text generation challenge for generative commonsense reasoning
Recently, large-scale pre-trained language models have demonstrated impressive
performance on several commonsense-reasoning benchmark datasets. However, building …
performance on several commonsense-reasoning benchmark datasets. However, building …
You only prompt once: On the capabilities of prompt learning on large language models to tackle toxic content
The spread of toxic content online is an important problem that has adverse effects on user
experience online and in our society at large. Motivated by the importance and impact of the …
experience online and in our society at large. Motivated by the importance and impact of the …
Mind the style of text! adversarial and backdoor attacks based on text style transfer
Adversarial attacks and backdoor attacks are two common security threats that hang over
deep learning. Both of them harness task-irrelevant features of data in their implementation …
deep learning. Both of them harness task-irrelevant features of data in their implementation …
Towards facilitating empathic conversations in online mental health support: A reinforcement learning approach
Online peer-to-peer support platforms enable conversations between millions of people who
seek and provide mental health support. If successful, web-based mental health …
seek and provide mental health support. If successful, web-based mental health …