TY - GEN
T1 - From Role-Play to Drama-Interaction
T2 - Findings of the 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024
AU - Wu, Weiqi
AU - Wu, Hongqiu
AU - Jiang, Lai
AU - Liu, Xingyuan
AU - Zhao, Hai
AU - Zhang, Min
N1 - Publisher Copyright:
© 2024 Association for Computational Linguistics.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85203155644
U2 - 10.18653/v1/2024.findings-acl.196
DO - 10.18653/v1/2024.findings-acl.196
M3 - 会议稿件
AN - SCOPUS:85203155644
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 3271
EP - 3290
BT - The 62nd Annual Meeting of the Association for Computational Linguistics
A2 - Ku, Lun-Wei
A2 - Martins, Andre
A2 - Srikumar, Vivek
PB - Association for Computational Linguistics (ACL)
Y2 - 11 August 2024 through 16 August 2024
ER -