The paper presents a new LLM‑based narrative platform that allows interchangeable Experience Managers (EMs) to operate over a shared symbolic world model, enabling explicit preconditions and effects for every operation. By representing each session as a plan in a common state‑transition system, the authors evaluate three different managers—open generation, Monte Carlo repair, and autonomous characters—on four properties: player agency, EM controllability, author intent, and robustness, using an interactive Little Red Riding Hood scenario. The results demonstrate that no single manager excels in all properties, providing authors and designers with concrete criteria to choose a manager that best fits their priorities.
By Jules Clerc (Heudiasyc), Domitile Lourdeaux (Heudiasyc), Mohamed Sallak (Heudiasyc), Marc Ravaine
arXiv:2608. 04037v1 Announce Type: cross Abstract: Designing narrative-grounded interactive experiences remains labor-intensive because interactive content must align with the underlying world implied by the narrative.
By Yi-Chun Chen
The paper introduces Forking Garden, a branching game generation system that threads narrative archetype as a persistent semantic signal throughout the generation pipeline. Narrative progression is modeled with soft Rise/Fall states, guiding the creation of plot nodes, structural constraints, encounter composition, objectives, rewards, and difficulty adaptation. Experiments across ten storylines show that the system produces distinct archetypal trajectories, improves entity diversity, and that Rise/Fall distinctions remain meaningful during play, aiding both narrative understanding and creator interpretation.
By Yunge Wen, Chenliang Huang, Hangyu Zhou, Zhuo Zeng, Yuxuan Weng, Timothy Merino, Julian Togelius, Max Kreminski, Sam Earle
arXiv:2601.15295v2 Announce Type: replace-cross
Abstract: Interactive narrative (IN) authors craft spaces of divergent narrative possibilities for players to explore, with the player's input determin...
By Yi Wang, John Joon Young Chung, Melissa Roemmele, Yuqian Sun, Tiffany Wang, Shm Garanganao Almeda, Brett A. Halperin, Yuwen Lu, Max Kreminski
arXiv:2608. 12336v1 Announce Type: cross Abstract: A story premise is the creative spark from which a full narrative can grow.
By Yang Yang, Zining Zhong, Qian Cao, Jindong Li, Boyun Xu, Kaishen Yuan, Menglin Yang, Yutao Yue
The paper introduces a framework that learns readerly dynamics—how readers respond over time—from high‑quality human stories and uses these dynamics to steer large language model (LLM) story generation. Instead of modeling full story content, a small LLM predicts low‑dimensional trajectories of future reader responses, which a larger, instruction‑following writer LLM then follows to produce story segments. Experiments show the approach improves trajectory‑based fidelity to human stories by 12%–35% while largely maintaining coherence.
By Danrui Li, Yiwei Zhao, Mubbasir Kapadia, Lingxiao Li