# ScriptWriter: Narrative-Guided Script Generation

arXiv: https://arxiv.org/abs/2005.10331 · HTML: https://mlsanity.com/paper/2005.10331/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 May 2020.

## Built on by (most cited first, 15 of 15)

- [One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles](https://mlsanity.com/paper/2108.09355/) (2021)
- [Unsupervised Enrichment of Persona-grounded Dialog with Background Stories](https://mlsanity.com/paper/2106.08364/) (2021)
- [Learning Implicit User Profiles for Personalized Retrieval-Based Chatbot](https://mlsanity.com/paper/2108.07935/) (2021)
- [Proactive Retrieval-based Chatbots based on Relevant Knowledge and Goals](https://mlsanity.com/paper/2107.08329/) (2021)
- [Mutation-Based Adversarial Attacks on Neural Text Detectors](https://mlsanity.com/paper/2302.05794/) (2023)
- [Movie101v2: Improved Movie Narration Benchmark](https://mlsanity.com/paper/2404.13370/) (2024)
- [Neural Sentence Ordering Based on Constraint Graphs](https://mlsanity.com/paper/2101.11178/) (2021)
- [GenHSI: Controllable Generation of Human-Scene Interaction Videos](https://mlsanity.com/paper/2506.19840/) (2025)
- [Controlled Cue Generation for Play Scripts](https://mlsanity.com/paper/2112.06953/) (2021)
- [BERT4SO: Neural Sentence Ordering by Fine-tuning BERT](https://mlsanity.com/paper/2103.13584/) (2021)
- [VScript: Controllable Script Generation with Visual Presentation](https://mlsanity.com/paper/2203.00314/) (2022)
- [Computational Storytelling and Emotions: A Survey](https://mlsanity.com/paper/2205.10967/) (2022)
- [Sudowoodo: a Chinese Lyric Imitation System with Source Lyrics](https://mlsanity.com/paper/2308.04665/) (2023)
- [Pruned Graph Neural Network for Short Story Ordering](https://mlsanity.com/paper/2203.06778/) (2022)
- ["Kurosawa": A Script Writer's Assistant](https://mlsanity.com/paper/2308.03122/) (2023)

## Abstract (arXiv)

It is appealing to have a system that generates a story or scripts automatically from a story-line, even though this is still out of our reach. In dialogue systems, it would also be useful to drive dialogues by a dialogue plan. In this paper, we address a key problem involved in these applications -- guiding a dialogue by a narrative. The proposed model ScriptWriter selects the best response among the candidates that fit the context as well as the given narrative. It keeps track of what in the narrative has been said and what is to be said. A narrative plays a different role than the context (i.e., previous utterances), which is generally used in current dialogue systems. Due to the unavailability of data for this new application, we construct a new large-scale data collection GraphMovie from a movie website where end-users can upload their narratives freely when watching a movie. Experimental results on the dataset show that our proposed approach based on narratives significantly outperforms the baselines that simply use the narrative as a kind of context.