mlsanityData to 7 Oct 2026

MLD-EA: Check and Complete Narrative Coherence by Introducing Emotions and Actions

arXiv 2412.02897 ↗First posted 3 Dec 2024cs.CL cs.AIcited by 4

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Abstract (arXiv)

Narrative understanding and story generation are critical challenges in natural language processing (NLP), with much of the existing research focused on summarization and question-answering tasks. While previous studies have explored predicting plot endings and generating extended narratives, they often neglect the logical coherence within stories, leaving a significant gap in the field. To address this, we introduce the Missing Logic Detector by Emotion and Action (MLD-EA) model, which leverages large language models (LLMs) to identify narrative gaps and generate coherent sentences that integrate seamlessly with the story's emotional and logical flow. The experimental results demonstrate that the MLD-EA model enhances narrative understanding and story generation, highlighting LLMs' potential as effective logic checkers in story writing with logical coherence and emotional consistency. This work fills a gap in NLP research and advances border goals of creating more sophisticated and reliable story-generation systems.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 24 of its 55 references that are in the map. First posted on arXiv 3 Dec 2024.

Builds on

24 of 55 references.

References · 24

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12 more
  1. 2024LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworkscited by 178
  2. 2020A Knowledge-Enhanced Pretraining Model for Commonsense Story Generationcited by 116
  3. 2024A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methodscited by 101
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  8. 2023Improving Pacing in Long-Form Story Planningcited by 21
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 3.

4 papers.

  1. 2025Learning to Play Like Humans: A Framework for LLM Adaptation in Interactive Fiction Gamescited by 3
  2. 2026BiT-MCTS: A Theme-based Bidirectional MCTS Approach to Chinese Fiction Generationcited by 0
  3. 2026LLMs Should Incorporate Explicit Mechanisms for Human Empathycited by 0
  4. 2026Scaling Long-Form Story Generation via Narrative State Trackingcited by 0