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Found 13 papers, 6 papers with code
WHAT-IF: Exploring Branching Narratives by Meta-Prompting Large Language Models
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.
Bridging the Social & Technical Divide in Augmentative and Alternative Communication (AAC) Applications for Autistic Adults
Natural Language Processing (NLP) techniques are being used more frequently to improve high-tech Augmentative and Alternative Communication (AAC), but many of these techniques are integrated without the inclusion of the users' perspectives.
CALYPSO: LLMs as Dungeon Masters' Assistants
The role of a Dungeon Master, or DM, in the game Dungeons & Dragons is to perform multiple tasks simultaneously.
FIREBALL: A Dataset of Dungeons and Dragons Actual-Play with Structured Game State Information
Dungeons & Dragons (D&D) is a tabletop roleplaying game with complex natural language interactions between players and hidden state information.
Human-in-the-Loop Schema Induction
Schema induction builds a graph representation explaining how events unfold in a scenario.
Author as Character and Narrator: Deconstructing Personal Narratives from the r/AmITheAsshole Reddit Community
In the r/AmITheAsshole subreddit, people anonymously share first person narratives that contain some moral dilemma or conflict and ask the community to judge who is at fault (i. e., who is "the asshole").
CoRRPUS: Code-based Structured Prompting for Neurosymbolic Story Understanding
In this work, we capitalize on state-of-the-art Code-LLMs, such as Codex, to bootstrap the use of symbolic methods for tracking the state of stories and aiding in story understanding.
Dungeons and Dragons as a Dialog Challenge for Artificial Intelligence
In this paper, we frame D&D specifically as a dialogue system challenge, where the tasks are to both generate the next conversational turn in the game and predict the state of the game given the dialogue history.
$\rm{C {\small IS}}^2$: A Simplified Commonsense Inference Evaluation for Story Prose
Transformers have been showing near-human performance on a variety of tasks, but they are not without their limitations.
Goal-Directed Story Generation: Augmenting Generative Language Models with Reinforcement Learning
The advent of large pre-trained generative language models has provided a common framework for AI story generation via sampling the model to create sequences that continue the story.
Story Realization: Expanding Plot Events into Sentences
Neural network based approaches to automated story plot generation attempt to learn how to generate novel plots from a corpus of natural language plot summaries.
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Controllable Neural Story Plot Generation via Reward Shaping
Language-modeling--based approaches to story plot generation attempt to construct a plot by sampling from a language model (LM) to predict the next character, word, or sentence to add to the story.
Event Representations for Automated Story Generation with Deep Neural Nets
We then present a technique for automated story generation whereby we decompose the problem into the generation of successive events (event2event) and the generation of natural language sentences from events (event2sentence).
