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NarrativePlay: Interactive Narrative Understanding

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arxiv 2310.01459 v1 pith:7NTLRDYC submitted 2023-10-02 cs.CL cs.AIcs.HC

classification cs.CLcs.AIcs.HC
keywords characternarrativesnarrativenarrativeplaycharactersextractedsystemusers
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper, we introduce NarrativePlay, a novel system that allows users to role-play a fictional character and interact with other characters in narratives such as novels in an immersive environment. We leverage Large Language Models (LLMs) to generate human-like responses, guided by personality traits extracted from narratives. The system incorporates auto-generated visual display of narrative settings, character portraits, and character speech, greatly enhancing user experience. Our approach eschews predefined sandboxes, focusing instead on main storyline events extracted from narratives from the perspective of a user-selected character. NarrativePlay has been evaluated on two types of narratives, detective and adventure stories, where users can either explore the world or improve their favorability with the narrative characters through conversations.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. H2HTalk: Evaluating Large Language Models as Emotional Companion

    cs.CL 2025-07 conditional novelty 5.0 of 10

    H2HTalk is a new 4,650-scenario benchmark that scores LLM emotional companions on dialogue, memory, and itinerary planning, and finds models struggle with implicit needs and long-horizon memory.

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