Branching Narratives: Character Decision Points Detection
<|reference_start|>Branching Narratives: Character Decision Points Detection: This paper presents the Character Decision Points Detection (CHADPOD) task, a task of identification of points within narratives where characters make decisions that may significantly influence the story's direction. We propose a novel dataset based on CYOA-like games graphs to be used as a benchmark for such a task. We provide a comparative analysis of different models' performance on this task, including a couple of LLMs and several MLMs as baselines, achieving up to 89% accuracy. This underscores the complexity of narrative analysis, showing the challenges associated with understanding character-driven story dynamics. Additionally, we show how such a model can be applied to the existing text to produce linear segments divided by potential branching points, demonstrating the practical application of our findings in narrative analysis.<|reference_end|>
@article{tikhonov2024branching,
    title={Branching Narratives: Character Decision Points Detection},
    author={Alexey Tikhonov},
    journal={arXiv preprint arXiv:2405.07282},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.07282},
    primaryClass={cs.CL}
}