cs.AI updates on arXiv.org 09月08日
轻量级叙事驱动场景生成方法
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本文提出一种轻量级管道,将叙事提示转换为2D游戏场景,通过提取时间结构和空间关系,实现叙事驱动的场景生成。

arXiv:2509.04481v1 Announce Type: cross Abstract: Recent advances in large language models(LLMs) enable compelling story generation, but connecting narrative text to playable visual environments remains an open challenge in procedural content generation(PCG). We present a lightweight pipeline that transforms short narrative prompts into a sequence of 2D tile-based game scenes, reflecting the temporal structure of stories. Given an LLM-generated narrative, our system identifies three key time frames, extracts spatial predicates in the form of "Object-Relation-Object" triples, and retrieves visual assets using affordance-aware semantic embeddings from the GameTileNet dataset. A layered terrain is generated using Cellular Automata, and objects are placed using spatial rules grounded in the predicate structure. We evaluated our system in ten diverse stories, analyzing tile-object matching, affordance-layer alignment, and spatial constraint satisfaction across frames. This prototype offers a scalable approach to narrative-driven scene generation and lays the foundation for future work on multi-frame continuity, symbolic tracking, and multi-agent coordination in story-centered PCG.

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场景生成 叙事驱动 大语言模型 游戏设计
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