mlsanityData to 7 Oct 2026

SWAG: Storytelling With Action Guidance

arXiv 2402.03483 ↗First posted 5 Feb 2024cs.CL cs.AIcited by 8

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Abstract (arXiv)

Automated long-form story generation typically employs long-context large language models (LLMs) for one-shot creation, which can produce cohesive but not necessarily engaging content. We introduce Storytelling With Action Guidance (SWAG), a novel approach to storytelling with LLMs. Our approach frames story writing as a search problem through a two-model feedback loop: one LLM generates story content, and another auxiliary LLM is used to choose the next best "action" to steer the story's future direction. Our results show that SWAG can substantially outperform previous end-to-end story generation techniques when evaluated by GPT-4 and through human evaluation. Our SWAG pipeline using only small open-source models surpasses GPT-3.5-Turbo.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 26 of its 39 references that are in the map. First posted on arXiv 5 Feb 2024.

Builds on

26 of 39 references.

References · 26

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023GPT-4 Technical Reportcited by 18,132
  3. 2017Proximal Policy Optimization Algorithmscited by 14,441
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  5. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  6. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  7. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
  8. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,769
  9. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  10. 2023FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioningcited by 2,551
  11. 2018Hierarchical Neural Story Generationcited by 1,182
  12. 2023AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedbackcited by 738
14 more
  1. 2021Learning How to Ask: Querying LMs with Mixtures of Soft Promptscited by 376
  2. 2020PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Trackingcited by 104
  3. 2018Controllable Neural Story Plot Generation via Reward Shapingcited by 49
  4. 2023Learning to Generate Better Than Your LLMcited by 49
  5. 2019Plan, Write, and Revise: an Interactive System for Open-Domain Story Generationcited by 43
  6. 2018A Skeleton-Based Model for Promoting Coherence Among Sentences in Narrative Story Generationcited by 42
  7. 2021Wordcraft: a Human-AI Collaborative Editor for Story Writingcited by 41
  8. 2021Controllable Generation from Pre-trained Language Models via Inverse Promptingcited by 29
  9. 2021Automatic Story Generation: Challenges and Attemptscited by 28
  10. 2021Plug-and-Blend: A Framework for Controllable Story Generation with Blended Control Codescited by 19
  11. 2021Goal-Directed Story Generation: Augmenting Generative Language Models with Reinforcement Learningcited by 14
  12. 2022Robust Preference Learning for Storytelling via Contrastive Reinforcement Learningcited by 14
  13. 2023End-to-end Story Plot Generatorcited by 7
  14. 2021A Temporal Variational Model for Story Generationcited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 0; 2026: 4.

8 papers.

  1. 2024Preference Optimization with Multi-Sample Comparisonscited by 16
  2. 2024Scaling Properties of Diffusion Models for Perceptual Taskscited by 15
  3. 2024Assessing Language Models' Worldview for Fiction Generationcited by 3
  4. 2026Interrupting the Loop: Periodic Subject Changes Raise Judged Surprise and Connection in Base Language Modelscited by 2
  5. 2024WHAT-IF: Exploring Branching Narratives by Meta-Prompting Large Language Modelscited by 0
  6. 2026LLMs Should Incorporate Explicit Mechanisms for Human Empathycited by 0
  7. 2026POLARIS: Guiding Small Models to Write Long Storiescited by 0
  8. 2026Scaling Long-Form Story Generation via Narrative State Trackingcited by 0