# Automatic Story Generation: Challenges and Attempts

arXiv: https://arxiv.org/abs/2102.12634 · HTML: https://mlsanity.com/paper/2102.12634/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- Builds on 32 of its 58 references that are in the map.
- First posted on arXiv 25 Feb 2021.

## Builds on (most cited first, 30 of 32)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Graph Attention Networks](https://mlsanity.com/paper/1710.10903/) (2017)
- [Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering](https://mlsanity.com/paper/1809.02789/) (2018)
- [CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge](https://mlsanity.com/paper/1811.00937/) (2018)
- [Hierarchical Neural Story Generation](https://mlsanity.com/paper/1805.04833/) (2018)
- [ConceptNet 5.5: An Open Multilingual Graph of General Knowledge](https://mlsanity.com/paper/1612.03975/) (2016)
- [Defending Against Neural Fake News](https://mlsanity.com/paper/1905.12616/) (2019)
- [COMET: Commonsense Transformers for Automatic Knowledge Graph Construction](https://mlsanity.com/paper/1906.05317/) (2019)
- [Skip-Thought Vectors](https://mlsanity.com/paper/1506.06726/) (2015)
- [Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning](https://mlsanity.com/paper/1909.00277/) (2019)
- [Plan-And-Write: Towards Better Automatic Storytelling](https://mlsanity.com/paper/1811.05701/) (2018)
- [A Simple Method for Commonsense Reasoning](https://mlsanity.com/paper/1806.02847/) (2018)
- [Commonsense Knowledge Mining from Pretrained Models](https://mlsanity.com/paper/1909.00505/) (2019)
- [Strategies for Structuring Story Generation](https://mlsanity.com/paper/1902.01109/) (2019)
- [A Knowledge-Enhanced Pretraining Model for Commonsense Story Generation](https://mlsanity.com/paper/2001.05139/) (2020)
- [PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking](https://mlsanity.com/paper/2004.14967/) (2020)
- [GLUCOSE: GeneraLized and COntextualized Story Explanations](https://mlsanity.com/paper/2009.07758/) (2020)
- [Deep Reinforcement Learning for Mention-Ranking Coreference Models](https://mlsanity.com/paper/1609.08667/) (2016)
- [Event Representations for Automated Story Generation with Deep Neural Nets](https://mlsanity.com/paper/1706.01331/) (2017)
- [Story Ending Generation with Incremental Encoding and Commonsense Knowledge](https://mlsanity.com/paper/1808.10113/) (2018)
- [Controllable Neural Story Plot Generation via Reward Shaping](https://mlsanity.com/paper/1809.10736/) (2018)
- [Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge](https://mlsanity.com/paper/1805.07858/) (2018)
- [Modeling Protagonist Emotions for Emotion-Aware Storytelling](https://mlsanity.com/paper/2010.06822/) (2020)
- [The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task](https://mlsanity.com/paper/1702.01841/) (2017)
- [Automated Storytelling via Causal, Commonsense Plot Ordering](https://mlsanity.com/paper/2009.00829/) (2020)
- [MCScript: A Novel Dataset for Assessing Machine Comprehension Using Script Knowledge](https://mlsanity.com/paper/1803.05223/) (2018)
- [Paragraph-level Commonsense Transformers with Recurrent Memory](https://mlsanity.com/paper/2010.01486/) (2020)
- [Dynamic Entity Representations in Neural Language Models](https://mlsanity.com/paper/1708.00781/) (2017)
- [Narrative Interpolation for Generating and Understanding Stories](https://mlsanity.com/paper/2008.07466/) (2020)

## Built on by (most cited first, 28 of 28)

- [Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionals](https://mlsanity.com/paper/2209.14958/) (2022)
- [Of Human Criteria and Automatic Metrics: A Benchmark of the Evaluation of Story Generation](https://mlsanity.com/paper/2208.11646/) (2022)
- [Agents' Room: Narrative Generation through Multi-step Collaboration](https://mlsanity.com/paper/2410.02603/) (2024)
- [Do Language Models Enjoy Their Own Stories? Prompting Large Language Models for Automatic Story Evaluation](https://mlsanity.com/paper/2405.13769/) (2024)
- [Leveraging Large Language Models for Learning Complex Legal Concepts through Storytelling](https://mlsanity.com/paper/2402.17019/) (2024)
- [Open-world Story Generation with Structured Knowledge Enhancement: A Comprehensive Survey](https://mlsanity.com/paper/2212.04634/) (2022)
- [COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective](https://mlsanity.com/paper/2305.05191/) (2023)
- [Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challenges](https://mlsanity.com/paper/2405.15604/) (2024)
- [GROVE: A Retrieval-augmented Complex Story Generation Framework with A Forest of Evidence](https://mlsanity.com/paper/2310.05388/) (2023)
- [LongStory: Coherent, Complete and Length Controlled Long story Generation](https://mlsanity.com/paper/2311.15208/) (2023)
- [CharacterGPT: A Persona Reconstruction Framework for Role-Playing Agents](https://mlsanity.com/paper/2405.19778/) (2024)
- [STORYTELLER: An Enhanced Plot-Planning Framework for Coherent and Cohesive Story Generation](https://mlsanity.com/paper/2506.02347/) (2025)
- [SWAG: Storytelling With Action Guidance](https://mlsanity.com/paper/2402.03483/) (2024)
- [CHAE: Fine-Grained Controllable Story Generation with Characters, Actions and Emotions](https://mlsanity.com/paper/2210.05221/) (2022)
- [HistAlign: Improving Context Dependency in Language Generation by Aligning with History](https://mlsanity.com/paper/2305.04782/) (2023)
- [Every picture tells a story: Image-grounded controllable stylistic story generation](https://mlsanity.com/paper/2209.01638/) (2022)
- [Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A Survey](https://mlsanity.com/paper/2602.15851/) (2026)
- [Exploring Story Generation with Multi-task Objectives in Variational Autoencoders](https://mlsanity.com/paper/2111.08133/) (2021)
- [Returning to the Start: Generating Narratives with Related Endpoints](https://mlsanity.com/paper/2404.00829/) (2024)
- [LLM Augmentations to support Analytical Reasoning over Multiple Documents](https://mlsanity.com/paper/2411.16116/) (2024)
- [Psychology-guided Controllable Story Generation](https://mlsanity.com/paper/2210.07493/) (2022)
- [Automatic Generation of German Drama Texts Using Fine Tuned GPT-2 Models](https://mlsanity.com/paper/2301.03119/) (2023)
- [Beyond Generative Artificial Intelligence: Roadmap for Natural Language Generation](https://mlsanity.com/paper/2407.10554/) (2024)
- [Guiding Generative Storytelling with Knowledge Graphs](https://mlsanity.com/paper/2505.24803/) (2025)
- [Automatic Emotion Modelling in Written Stories](https://mlsanity.com/paper/2212.11382/) (2022)
- [Sudowoodo: a Chinese Lyric Imitation System with Source Lyrics](https://mlsanity.com/paper/2308.04665/) (2023)
- [CreAgentive: An Agent Workflow Driven Multi-Category Creative Generation Engine](https://mlsanity.com/paper/2509.26461/) (2025)
- [AgentEval: Generative Agents as Reliable Proxies for Human Evaluation of AI-Generated Content](https://mlsanity.com/paper/2512.08273/) (2025)

## Abstract (arXiv)

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.