WHAT-IF: Exploring Branching Narratives by Meta-Prompting Large Language Models

AmazUtah_NLP at SemEval-2024 Task 9: A MultiChoice Question Answering System for Commonsense Defying Reasoning


View a PDF of the paper titled WHAT-IF: Exploring Branching Narratives by Meta-Prompting Large Language Models, by Runsheng “Anson” Huang and Lara J. Martin and Chris Callison-Burch

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Abstract:WHAT-IF — Writing a Hero’s Alternate Timeline through Interactive Fiction — is a system that uses zero-shot meta-prompting to create branching narratives from a prewritten story. Played as an interactive fiction (IF) game, WHAT-IF lets the player choose between decisions that the large language model (LLM) GPT-4 generates as possible branches in the story. Starting with an existing linear plot as input, a branch is created at each key decision taken by the main character. By meta-prompting the LLM to consider the major plot points from the story, the system produces coherent and well-structured alternate storylines. WHAT-IF stores the branching plot tree in a graph which helps it to both keep track of the story for prompting and maintain the structure for the final IF system. A video demo of our system can be found here: this https URL.

Submission history

From: Lara J. Martin [view email]
[v1]
Fri, 13 Dec 2024 21:48:54 UTC (8,536 KB)
[v2]
Tue, 17 Dec 2024 15:56:50 UTC (8,535 KB)



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