A survey of controllable text generation using transformer-based pre-trained language models

H Zhang, H Song, S Li, M Zhou, D Song - ACM Computing Surveys, 2023 - dl.acm.org
Controllable Text Generation (CTG) is an emerging area in the field of natural language
generation (NLG). It is regarded as crucial for the development of advanced text generation …

A complete survey on generative ai (aigc): Is chatgpt from gpt-4 to gpt-5 all you need?

C Zhang, C Zhang, S Zheng, Y Qiao, C Li… - arXiv preprint arXiv …, 2023 - arxiv.org
As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …

Language models with image descriptors are strong few-shot video-language learners

Z Wang, M Li, R Xu, L Zhou, J Lei… - Advances in …, 2022 - proceedings.neurips.cc
The goal of this work is to build flexible video-language models that can generalize to
various video-to-text tasks from few examples. Existing few-shot video-language learners …

Pretrained language models for text generation: A survey

J Li, T Tang, WX Zhao, JY Nie, JR Wen - arXiv preprint arXiv:2201.05273, 2022 - arxiv.org
Text Generation aims to produce plausible and readable text in a human language from
input data. The resurgence of deep learning has greatly advanced this field, in particular …

Galaxy: A generative pre-trained model for task-oriented dialog with semi-supervised learning and explicit policy injection

W He, Y Dai, Y Zheng, Y Wu, Z Cao, D Liu… - Proceedings of the …, 2022 - ojs.aaai.org
Pre-trained models have proved to be powerful in enhancing task-oriented dialog systems.
However, current pre-training methods mainly focus on enhancing dialog understanding …

Evaluation of text generation: A survey

A Celikyilmaz, E Clark, J Gao - arXiv preprint arXiv:2006.14799, 2020 - arxiv.org
The paper surveys evaluation methods of natural language generation (NLG) systems that
have been developed in the last few years. We group NLG evaluation methods into three …

TOD-BERT: Pre-trained natural language understanding for task-oriented dialogue

CS Wu, S Hoi, R Socher, C Xiong - arXiv preprint arXiv:2004.06871, 2020 - arxiv.org
The underlying difference of linguistic patterns between general text and task-oriented
dialogue makes existing pre-trained language models less useful in practice. In this work …

Ubar: Towards fully end-to-end task-oriented dialog system with gpt-2

Y Yang, Y Li, X Quan - Proceedings of the AAAI Conference on Artificial …, 2021 - ojs.aaai.org
This paper presents our task-oriented dialog system UBAR which models task-oriented
dialogs on a dialog session level. Specifically, UBAR is acquired by fine-tuning the large pre …

Recent advances and challenges in task-oriented dialog systems

Z Zhang, R Takanobu, Q Zhu, ML Huang… - Science China …, 2020 - Springer
Due to the significance and value in human-computer interaction and natural language
processing, task-oriented dialog systems are attracting more and more attention in both …

Soloist: Building Task Bots at Scale with Transfer Learning and Machine Teaching

B Peng, C Li, J Li, S Shayandeh, L Liden… - Transactions of the …, 2021 - direct.mit.edu
We present a new method, Soloist, that uses transfer learning and machine teaching to build
task bots at scale. We parameterize classical modular task-oriented dialog systems using a …