Automatic Story Generation: Challenges and Attempts
arXiv:2102.12634
Abstract
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 generation addressed those challenges. 2. Discuss future research directions and new technologies that may aid more advancements. 3. Shed light on emerging and often overlooked challenges such as creativity and discourse.
References in corpus (10)
- ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
- Skip-Thought Vectors
- A Simple Method for Commonsense Reasoning
- Event Representations for Automated Story Generation with Deep Neural Nets
- Hierarchical Neural Story Generation
- A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories
- Controllable Neural Story Plot Generation via Reward Shaping
- Computational Narrative Intelligence: A Human-Centered Goal for Artificial Intelligence
- PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking
- Narrative Interpolation for Generating and Understanding Stories