# CollabStory: Multi-LLM Collaborative Story Generation and Authorship Analysis

arXiv: https://arxiv.org/abs/2406.12665 · HTML: https://mlsanity.com/paper/2406.12665/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 45 references that are in the map.
- First posted on arXiv 18 Jun 2024.

## Builds on (most cited first, 16 of 16)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [ALBERT: A Lite BERT for Self-supervised Learning of Language Representations](https://mlsanity.com/paper/1909.11942/) (2019)
- [Hierarchical Neural Story Generation](https://mlsanity.com/paper/1805.04833/) (2018)
- [OLMo: Accelerating the Science of Language Models](https://mlsanity.com/paper/2402.00838/) (2024)
- [CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities](https://mlsanity.com/paper/2201.06796/) (2022)
- [OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examples](https://mlsanity.com/paper/2307.11729/) (2023)
- [Help me write a poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing](https://mlsanity.com/paper/2210.13669/) (2022)
- [Shaping Human-AI Collaboration: Varied Scaffolding Levels in Co-writing with Language Models](https://mlsanity.com/paper/2402.11723/) (2024)
- [Few-Shot Detection of Machine-Generated Text using Style Representations](https://mlsanity.com/paper/2401.06712/) (2024)
- [From Text to Source: Results in Detecting Large Language Model-Generated Content](https://mlsanity.com/paper/2309.13322/) (2023)
- [A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Texts](https://mlsanity.com/paper/2311.08374/) (2023)
- [GhostWriter: Augmenting Collaborative Human-AI Writing Experiences Through Personalization and Agency](https://mlsanity.com/paper/2402.08855/) (2024)
- [Towards Automatic Boundary Detection for Human-AI Collaborative Hybrid Essay in Education](https://mlsanity.com/paper/2307.12267/) (2023)
- [Writing with AI Lowers Psychological Ownership, but Longer Prompts Can Help](https://mlsanity.com/paper/2404.03108/) (2024)

## Built on by (most cited first, 26 of 26)

- [HelloBench: Evaluating Long Text Generation Capabilities of Large Language Models](https://mlsanity.com/paper/2409.16191/) (2024)
- [X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs](https://mlsanity.com/paper/2505.16997/) (2025)
- [LLM Probability Concentration: How Alignment Shrinks the Generative Horizon](https://mlsanity.com/paper/2506.17871/) (2025)
- [Creativity in LLM-based Multi-Agent Systems: A Survey](https://mlsanity.com/paper/2505.21116/) (2025)
- [CoPL: Collaborative Preference Learning for Personalizing LLMs](https://mlsanity.com/paper/2503.01658/) (2025)
- [Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Research](https://mlsanity.com/paper/2506.01839/) (2025)
- [Frankentext: Stitching random text fragments into long-form narratives](https://mlsanity.com/paper/2505.18128/) (2025)
- [Optimizing Diversity and Quality through Base-Aligned Model Collaboration](https://mlsanity.com/paper/2511.05650/) (2025)
- [Collaborative Document Editing with Multiple Users and AI Agents](https://mlsanity.com/paper/2509.11826/) (2025)
- [ConlangCrafter: Constructing Languages with a Multi-Hop LLM Pipeline](https://mlsanity.com/paper/2508.06094/) (2025)
- [Evaluating the Creativity of LLMs in Persian Literary Text Generation](https://mlsanity.com/paper/2509.18401/) (2025)
- [DetectRL-X: Towards Reliable Multilingual and Real-World LLM-Generated Text Detection](https://mlsanity.com/paper/2605.15518/) (2026)
- [JRE-L: Journalist, Reader, and Editor LLMs in the Loop for Science Journalism for the General Audience](https://mlsanity.com/paper/2501.16865/) (2025)
- [Agentic Search Engine for Real-Time IoT Data](https://mlsanity.com/paper/2503.12255/) (2025)
- [Guiding Generative Storytelling with Knowledge Graphs](https://mlsanity.com/paper/2505.24803/) (2025)
- [A Review on Large Language Models for Visual Analytics](https://mlsanity.com/paper/2503.15176/) (2025)
- [ConspEmoLLM-v2: A robust and stable model to detect sentiment-transformed conspiracy theories](https://mlsanity.com/paper/2505.14917/) (2025)
- [HAMLET: A Hierarchical and Adaptive Multi-Agent Framework for Live Embodied Theatrics](https://mlsanity.com/paper/2507.15518/) (2025)
- [Story Ribbons: Reimagining Storyline Visualizations with Large Language Models](https://mlsanity.com/paper/2508.06772/) (2025)
- [A Flexible Multi-Agent LLM-Human Framework for Fast Human Validated Tool Building](https://mlsanity.com/paper/2512.01434/) (2025)
- [Codified Foreshadowing-Payoff Text Generation](https://mlsanity.com/paper/2601.07033/) (2026)
- [LLMs Should Incorporate Explicit Mechanisms for Human Empathy](https://mlsanity.com/paper/2604.10557/) (2026)
- [From Coarse to Fine: Benchmarking and Reward Modeling for Writing-Centric Generation Tasks](https://mlsanity.com/paper/2604.27453/) (2026)
- [Humans' ALMANAC: A Human Collaboration Dataset of Action-Level Mental Model Annotations for Agent Collaboration](https://mlsanity.com/paper/2606.06388/) (2026)
- [CASPER in the Machine: Insights into Character Variety in LLM-Generated Stories](https://mlsanity.com/paper/2606.22454/) (2026)
- [Scaling Long-Form Story Generation via Narrative State Tracking](https://mlsanity.com/paper/2609.35759/) (2026)

## Abstract (arXiv)

The rise of unifying frameworks that enable seamless interoperability of Large Language Models (LLMs) has made LLM-LLM collaboration for open-ended tasks a possibility. Despite this, there have not been efforts to explore such collaborative writing. We take the next step beyond human-LLM collaboration to explore this multi-LLM scenario by generating the first exclusively LLM-generated collaborative stories dataset called CollabStory. We focus on single-author to multi-author (up to 5 LLMs) scenarios, where multiple LLMs co-author stories. We generate over 32k stories using open-source instruction-tuned LLMs. Further, we take inspiration from the PAN tasks that have set the standard for human-human multi-author writing tasks and analysis. We extend their authorship-related tasks for multi-LLM settings and present baselines for LLM-LLM collaboration. We find that current baselines are not able to handle this emerging scenario. Thus, CollabStory is a resource that could help propel an understanding as well as the development of new techniques to discern the use of multiple LLMs. This is crucial to study in the context of writing tasks since LLM-LLM collaboration could potentially overwhelm ongoing challenges related to plagiarism detection, credit assignment, maintaining academic integrity in educational settings, and addressing copyright infringement concerns. We make our dataset and code available at https://github.com/saranya-venkatraman/CollabStory.