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.
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.
arXiv:2606. 13348v1 Announce Type: cross Abstract: Computational creativity in Interactive Fiction faces a fundamental tension: Large Language Models (LLM) may produce creative narratives but struggle with world coherence, while symbolic systems ensure consistency but lack creative flexibility.
arXiv:2608. 12336v1 Announce Type: cross Abstract: A story premise is the creative spark from which a full narrative can grow.
arXiv:2608. 15654v1 Announce Type: cross Abstract: Large language models can write fluent stories, but open-ended storytelling requires more than local fluency.
arXiv:2609.14677v1 Announce Type: new Abstract: Large language models (LLMs) have changed the way people engage with stories. Drawing on public chatbot logs, we can see that when users generate stori...
CriticaLLM is a fully automated Game Master framework that uses Large Language Models (LLMs) to run entire tabletop role‑playing games, from story creation to managing exploration and combat. The paper outlines key components LLMs should exhibit for TTRPGs and evaluates the system with real players, examining plot and antagonist diversity across four LLMs of different sizes. The results suggest that CriticaLLM is a promising option for automating TTRPG gameplay.
arXiv:2607. 00918v1 Announce Type: cross Abstract: Although large language models (LLMs) have demonstrated impressive creative fiction generation, they struggle to maintain narrative consistency and coherent plot lines in long-form stories.
arXiv:2610.32002v1 Announce Type: new Abstract: The rapid growth of microdramas has increased demand for high-quality script production. Long-form microdrama script generation with LLMs requires both...
arXiv:2607. 00527v1 Announce Type: new Abstract: Generative AI now enables games to produce dialogue, quests, characters, images, and worlds at runtime.
Video interactive storytelling enables viewers to actively steer how a video unfolds. However, once we allow viewers to intervene during generation, a new challenge arises: The viewer's request can ha...
arXiv:2606. 16014v1 Announce Type: cross Abstract: Many games rely on storytelling combined with systems that track levelling, NPC behaviour, and consequence simulation; bridging tightly-authored narrative with deeply-simulated worlds -- most acute in sandbox and open-world settings -- has been prohibitively expensive.
arXiv:2610.09326v1 Announce Type: new Abstract: Video interactive storytelling enables viewers to actively steer how a video unfolds. However, once we allow viewers to intervene during generation, a...