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This paper introduces SENSE, a framework leveraging AI to generate branching visual novels with complex emotional navigation and structural coherence. By integrating state-based narrative architecture with context management, the system demonstrates improved emotional fidelity and diversity in generated stories compared to baseline models.
SENSE: State-aware Emotion Navigation Storytelling Engine
arXiv:2610.07666v1 Announce Type: cross Abstract: This paper presents SENSE, a state-aware framework for generating playable branching visual novels with multi-track emotional navigation. Integrating a state-based narrative architecture called MIND, a structure analyzer, and a path-aware context management module, SENSE produces narratives that are both structurally coherent and emotionally rich. From minimal high-level inputs, it generates multiple intersecting routes while preserving character consistency and narrative causality. Evaluations using LLM judges, affective metrics, and visual assessments indicate SENSE outperforms baselines in narrative diversity and robust asset integration, while preliminary human trials show directional improvements in emotional fidelity alongside comparable enjoyment.
Abstract:This paper presents SENSE, a state-aware framework for generating playable branching visual novels with multi-track emotional navigation. Integrating a state-based narrative architecture called MIND, a structure analyzer, and a path-aware context management module, SENSE produces narratives that are both structurally coherent and emotionally rich. From minimal high-level inputs, it generates multiple intersecting routes while preserving character consistency and narrative causality. Evaluations using LLM judges, affective metrics, and visual assessments indicate SENSE outperforms baselines in narrative diversity and robust asset integration, while preliminary human trials show directional improvements in emotional fidelity alongside comparable enjoyment.
Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Multimedia (cs.MM)
arXiv:2610.07666 [cs.HC]
(or arXiv:2610.07666v1 [cs.HC] for this version)
https://doi.org/10.48550/arXiv.2610.07666 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
https://doi.org/10.1109/TG.2026.3733998 Focus to learn more DOI(s) linking to related resources
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