Automatic story generation: A survey of approaches

AI Alhussain, AM Azmi - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Computational generation of stories is a subfield of computational creativity where artificial
intelligence and psychology intersect to teach computers how to mimic humans' creativity. It …

How close is chatgpt to human experts? comparison corpus, evaluation, and detection

B Guo, X Zhang, Z Wang, M Jiang, J Nie, Y Ding… - arXiv preprint arXiv …, 2023 - arxiv.org
The introduction of ChatGPT has garnered widespread attention in both academic and
industrial communities. ChatGPT is able to respond effectively to a wide range of human …

Co-writing screenplays and theatre scripts with language models: Evaluation by industry professionals

P Mirowski, KW Mathewson, J Pittman… - Proceedings of the 2023 …, 2023 - dl.acm.org
Language models are increasingly attracting interest from writers. However, such models
lack long-range semantic coherence, limiting their usefulness for longform creative writing …

Re3: Generating longer stories with recursive reprompting and revision

K Yang, Y Tian, N Peng, D Klein - arXiv preprint arXiv:2210.06774, 2022 - arxiv.org
We consider the problem of automatically generating longer stories of over two thousand
words. Compared to prior work on shorter stories, long-range plot coherence and relevance …

Justifying recommendations using distantly-labeled reviews and fine-grained aspects

J Ni, J Li, J McAuley - Proceedings of the 2019 conference on …, 2019 - aclanthology.org
Several recent works have considered the problem of generating reviews (or 'tips') as a form
of explanation as to why a recommendation might match a customer's interests. While …

Automatic story generation: Challenges and attempts

A Alabdulkarim, S Li, X Peng - arXiv preprint arXiv:2102.12634, 2021 - arxiv.org
The scope of this survey paper is to explore the challenges in automatic story generation.
We hope to contribute in the following ways: 1. Explore how previous research in story …

Bold: Dataset and metrics for measuring biases in open-ended language generation

J Dhamala, T Sun, V Kumar, S Krishna… - Proceedings of the …, 2021 - dl.acm.org
Recent advances in deep learning techniques have enabled machines to generate
cohesive open-ended text when prompted with a sequence of words as context. While these …

Plug and play language models: A simple approach to controlled text generation

S Dathathri, A Madotto, J Lan, J Hung, E Frank… - arXiv preprint arXiv …, 2019 - arxiv.org
Large transformer-based language models (LMs) trained on huge text corpora have shown
unparalleled generation capabilities. However, controlling attributes of the generated …

The woman worked as a babysitter: On biases in language generation

E Sheng, KW Chang, P Natarajan, N Peng - arXiv preprint arXiv …, 2019 - arxiv.org
We present a systematic study of biases in natural language generation (NLG) by analyzing
text generated from prompts that contain mentions of different demographic groups. In this …

TaleBrush: Sketching stories with generative pretrained language models

JJY Chung, W Kim, KM Yoo, H Lee, E Adar… - Proceedings of the 2022 …, 2022 - dl.acm.org
While advanced text generation algorithms (eg, GPT-3) have enabled writers to co-create
stories with an AI, guiding the narrative remains a challenge. Existing systems often …