Oct 30, 2020 · In this paper, we study the novel problem of topic-preserving synthetic news generation. We propose a novel deep reinforcement learning-based method.

Oct 30, 2020 · Thus, it is important to study the problem of topic-preserving and realistic synthetic news generation. Moreover, fine-tuning language models ...

Abstract—The text generation methods have witnessed great success in text summarization, machine translation, and synthetic news generation.

Topic-preserving synthetic news generation: An adversarial deep reinforcement learning approach. A Mosallanezhad, K Shu, H Liu. arXiv preprint arXiv ...

Topic-Preserving Synthetic News Generation: An Adversarial Deep Reinforcement Learning Approach pdf: https://t.co/0lPZiBK7Jp abs: https://t.co/C9OAJ5EC3C.

In this paper we present a deep reinforcement learning approach to paraphrase generation. Specifically, we propose a new model for the task, which consists ...

Topic-Preserving Synthetic News Generation: An Adversarial Deep Reinforcement Learning Approach ... Deep Reinforcement Learning-based Text Anonymization ...

Text generation is a crucial task in NLP. Recently, several adversarial generative models have been proposed to improve the exposure bias problem in text ...

Topic-Preserving Synthetic News Generation: An Adversarial Deep Reinforcement Learning Approach ... Deep Reinforcement Learning-based Text Anonymization ...

Topic-preserving synthetic news generation: An adversarial deep reinforcement learning approach. A Mosallanezhad, K Shu, H Liu arXiv preprint arXiv ...