# Cue Me In: Content-Inducing Approaches to Interactive Story Generation

arXiv: https://arxiv.org/abs/2010.09935 · HTML: https://mlsanity.com/paper/2010.09935/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Oct 2020.

## Built on by (most cited first, 16 of 16)

- [Generating Long-form Story Using Dynamic Hierarchical Outlining with Memory-Enhancement](https://mlsanity.com/paper/2412.13575/) (2024)
- [Prototypical Human-AI Collaboration Behaviors from LLM-Assisted Writing in the Wild](https://mlsanity.com/paper/2505.16023/) (2025)
- [Open-world Story Generation with Structured Knowledge Enhancement: A Comprehensive Survey](https://mlsanity.com/paper/2212.04634/) (2022)
- [Persona-Guided Planning for Controlling the Protagonist's Persona in Story Generation](https://mlsanity.com/paper/2204.10703/) (2022)
- [Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation](https://mlsanity.com/paper/2104.05801/) (2021)
- [Towards Inter-character Relationship-driven Story Generation](https://mlsanity.com/paper/2211.00676/) (2022)
- [DiSCoL: Toward Engaging Dialogue Systems through Conversational Line Guided Response Generation](https://mlsanity.com/paper/2102.02191/) (2021)
- [StoryDB: Broad Multi-language Narrative Dataset](https://mlsanity.com/paper/2109.14396/) (2021)
- [PASTA: A Dataset for Modeling Participant States in Narratives](https://mlsanity.com/paper/2208.00329/) (2022)
- [Controlled Cue Generation for Play Scripts](https://mlsanity.com/paper/2112.06953/) (2021)
- [LyricJam: A system for generating lyrics for live instrumental music](https://mlsanity.com/paper/2106.01960/) (2021)
- [Grounded Keys-to-Text Generation: Towards Factual Open-Ended Generation](https://mlsanity.com/paper/2212.01956/) (2022)
- [Adversarial Transformer Language Models for Contextual Commonsense Inference](https://mlsanity.com/paper/2302.05406/) (2023)
- [AfriKI: Machine-in-the-Loop Afrikaans Poetry Generation](https://mlsanity.com/paper/2103.16190/) (2021)
- [Can Language Models Take A Hint? Prompting for Controllable Contextualized Commonsense Inference](https://mlsanity.com/paper/2410.02202/) (2024)
- [Tinker Tales: Interactive Storytelling Framework for Early Childhood Narrative Development and AI Literacy](https://mlsanity.com/paper/2504.13969/) (2025)

## Abstract (arXiv)

Automatically generating stories is a challenging problem that requires producing causally related and logical sequences of events about a topic. Previous approaches in this domain have focused largely on one-shot generation, where a language model outputs a complete story based on limited initial input from a user. Here, we instead focus on the task of interactive story generation, where the user provides the model mid-level sentence abstractions in the form of cue phrases during the generation process. This provides an interface for human users to guide the story generation. We present two content-inducing approaches to effectively incorporate this additional information. Experimental results from both automatic and human evaluations show that these methods produce more topically coherent and personalized stories compared to baseline methods.