arXiv (All)
open access
Do Large Language Models Always Tell The Same Stories?
Recent advances in large language models (LLMs) have enabled the generation of high-quality prose, yet whether these models are capable of generating diverse or creative artifacts remains a contested question. In this work, we investigate the diversity of LLM-generated stories through the framework
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Do Large Language Models Always Tell The Same Stories?#919869
- Narrative Flattening: How Post-Training Compresses Thematic, Affective, and Stylistic Variation in LLM Fiction#985105
- LitSeg: Narrative-Aware Document Segmentation for Literary RAG#974437
- Large Language Models Substantially Compress Well-Being Inequality but Largely Preserve Its Socioeconomic Structure#1117767
- POLARIS: Guiding Small Models to Write Long Stories#798938
Record · ID 924098
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive