From Role-Play to Drama-Interaction: An LLM Solution

Weiqi Wu, Hongqiu Wu, Lai Jiang, Xingyuan Liu, Hai Zhao, Min Zhang


Abstract
Drama is a form of storytelling inspired by human creativity, proceeding with a predefined storyline, carrying emotions and thoughts.This paper introduces LLM-based interactive drama, which endows traditional drama with an unprecedented immersion, where a person is allowed to walk into it and interact with the characters and scenes.We define this new artistic genre by 6 essential elements—plot, character, thought, diction, spectacle and interaction—and study the entire pipeline to forge a backbone drama LLM to drive the playing process, which is challenged by limited drama resources, uncontrollable narrative development, and complicated instruction following.We propose Narrative Chain to offer finer control over the narrative progression during interaction with players;Auto-Drama to synthesize drama scripts given arbitrary stories;Sparse Instruction Tuning to allow the model to follow sophisticated instructions.We manually craft 3 scripts, Detective Conan, Harry Potter, Romeo and Juliet, and design a 5-dimension principle to evaluate the drama LLM comprehensively.
Anthology ID:
2024.findings-acl.196
Volume:
Findings of the Association for Computational Linguistics ACL 2024
Month:
August
Year:
2024
Address:
Bangkok, Thailand and virtual meeting
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3271–3290
Language:
URL:
https://aclanthology.org/2024.findings-acl.196
DOI:
Bibkey:
Cite (ACL):
Weiqi Wu, Hongqiu Wu, Lai Jiang, Xingyuan Liu, Hai Zhao, and Min Zhang. 2024. From Role-Play to Drama-Interaction: An LLM Solution. In Findings of the Association for Computational Linguistics ACL 2024, pages 3271–3290, Bangkok, Thailand and virtual meeting. Association for Computational Linguistics.
Cite (Informal):
From Role-Play to Drama-Interaction: An LLM Solution (Wu et al., Findings 2024)
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PDF:
https://aclanthology.org/2024.findings-acl.196.pdf