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LLM-Based Story Generation Aligned with Narrative Structure

원문정보

서사 구조를 따르는 LLM 기반 스토리 생성 연구

Eunsu Ji, Tae-Kyung Yoo

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초록

영어

This study proposes a structured story generation system based on traditional narrative theory using a large language model (LLM). The proposed system sequentially constructs a three-act structure and a 15-step narrative structure of "Save the Cat!" based on the log line, character information, and genre input by the user, and each step is embodied through hierarchical generation and prompt chaining. In particular, when user modifications occur, the changes are designed to be automatically reflected in the upper and lower stages to maintain narrative consistency and logic. To verify the effectiveness of this system, human-written narratives, single-prompt-based generative narratives, and generative narratives from the proposed system were compared and evaluated, yielding excellent results in terms of narrative structure fidelity and logic. By demonstrating the structural controllability of LLM-based story generation, this study suggests applicability in the field of digital content production in the future.

목차

ABSTRACT
1. 서론
1.1 연구 목적 및 필요성
1.2 연구 방법 및 범위
2. 관련 연구
2.1 서사 구조 이론
2.2 대규모 언어 모델(LLM)
2.3 LLM 기반 스토리 창작 도구
3. 구조 설계 및 구현
3.1 시스템 개요
3.2 사용자 입력
3.3 스토리 단계별 생성
3.4 프롬프트 체이닝
4. 실험 설계
4.1 실험 목적
4.2 생성 방식에 따른 이야기 품질 평가
4.3 LLM에 따른 스토리 생성 품질 평가
4.4 생성 방식에 따른 이야기 내 구성 요소 비율 평가
5. 결론
Acknowledgement
참고문헌

저자정보

  • Eunsu Ji Graduate School of Advance Imaging Science, Chung-Ang University Seoul, Korea
  • Tae-Kyung Yoo Chung-Ang University Seoul, Korea

참고문헌

자료제공 : 네이버학술정보

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