STORYTELLER: An Enhanced Plot-Planning Framework for Coherent and Cohesive Story Generation
Not on the map. Why?
Abstract (arXiv)
Stories are central to human culture, serving to share ideas, preserve traditions, and foster connections. Automatic story generation, a key advancement in artificial intelligence (AI), offers new possibilities for creating personalized content, exploring creative ideas, and enhancing interactive experiences. However, existing methods struggle to maintain narrative coherence and logical consistency. This disconnect compromises the overall storytelling experience, underscoring the need for substantial improvements. Inspired by human cognitive processes, we introduce Storyteller, a novel approach that systemically improves the coherence and consistency of automatically generated stories. Storyteller introduces a plot node structure based on linguistically grounded subject verb object (SVO) triplets, which capture essential story events and ensure a consistent logical flow. Unlike previous methods, Storyteller integrates two dynamic modules, the STORYLINE and narrative entity knowledge graph (NEKG),that continuously interact with the story generation process. This integration produces structurally sound, cohesive and immersive narratives. Extensive experiments demonstrate that Storyteller significantly outperforms existing approaches, achieving an 84.33% average win rate through human preference evaluation. At the same time, it is also far ahead in other aspects including creativity, coherence, engagement, and relevance.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 26 of its 40 references that are in the map. First posted on arXiv 3 Jun 2025.
Builds on
26 of 40 references.
References · 26
- 2017Attention Is All You Needcited by 60,361
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2023GPT-4 Technical Reportcited by 18,396
- 2024The Llama 3 Herd of Modelscited by 14,715
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
- 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,944
- 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,512
- 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,234
- 2021Calibrate Before Use: Improving Few-Shot Performance of Language Modelscited by 1,392
- 2018Hierarchical Neural Story Generationcited by 1,193
- 2023LIMA: Less Is More for Alignmentcited by 1,100
14 more
- 2015A Diversity-Promoting Objective Function for Neural Conversation Modelscited by 1,077
- 2022A Survey on In-context Learningcited by 721
- 2024From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipelinecited by 500
- 2018Plan-And-Write: Towards Better Automatic Storytellingcited by 234
- 2022Re3: Generating Longer Stories With Recursive Reprompting and Revisioncited by 193
- 2022Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionalscited by 191
- 2024LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMscited by 144
- 2019Strategies for Structuring Story Generationcited by 124
- 2020A Knowledge-Enhanced Pretraining Model for Commonsense Story Generationcited by 116
- 2020PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Trackingcited by 105
- 2021Inferring the Reader: Guiding Automated Story Generation with Commonsense Reasoningcited by 29
- 2021Automatic Story Generation: Challenges and Attemptscited by 28
- 2022Open-world Story Generation with Structured Knowledge Enhancement: A Comprehensive Surveycited by 22
- 2021Guiding Neural Story Generation with Reader Modelscited by 12
Built on by
Citing papers per year: 2025: 2; 2026: 8.
10 papers.
- 2026Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A Surveycited by 5
- 2026Interrupting the Loop: Periodic Subject Changes Raise Judged Surprise and Connection in Base Language Modelscited by 2
- 2026AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessmentcited by 1
- 2026StoryLens: Preference-Aligned Story Rewriting via Context-Aware Narrative Enrichmentcited by 1
- 2025CreAgentive: An Agent Workflow Driven Multi-Category Creative Generation Enginecited by 0
- 2025Telling Speculative Stories to Help Humans Imagine the Harms of Healthcare AIcited by 0
- 2026Characterizing Cultural Localization in AI-Generated Storiescited by 0
- 2026Steering Emotional Dynamics for Art Therapy: Controllable Narrative Script Generation through Hierarchically Guided LLM Agentscited by 0
- 2026Scaling Long-Form Story Generation via Narrative State Trackingcited by 0
- 2026Narrative Lookahead in LLMs: Event-Level Decodability, Predictive Advantage, and Steeringcited by 0
- 2026Narrative Lookahead in LLMs: Event-Level Decodability, Predictive Advantage, and Steering13 Oct 2026
- 2026Scaling Long-Form Story Generation via Narrative State Tracking28 Sep 2026
- 2026Interrupting the Loop: Periodic Subject Changes Raise Judged Surprise and Connection in Base Language Models20 Aug 2026
- 2026Steering Emotional Dynamics for Art Therapy: Controllable Narrative Script Generation through Hierarchically Guided LLM Agents15 Jun 2026
- 2026Characterizing Cultural Localization in AI-Generated Stories12 Jun 2026
- 2026StoryLens: Preference-Aligned Story Rewriting via Context-Aware Narrative Enrichment27 May 2026
- 2026AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessment20 Apr 2026
- 2026Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A Survey23 Jan 2026
- 2025Telling Speculative Stories to Help Humans Imagine the Harms of Healthcare AI16 Oct 2025
- 2025CreAgentive: An Agent Workflow Driven Multi-Category Creative Generation Engine30 Sep 2025