Summary of Assessing Language Models’ Worldview For Fiction Generation, by Aisha Khatun and Daniel G. Brown
Assessing Language Models’ Worldview for Fiction Generation
by Aisha Khatun, Daniel G. Brown
First submitted to arxiv on: 15 Aug 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This study investigates the suitability of Large Language Models (LLMs) in generating fiction. The researchers posed questions to nine LLMs, finding that only two models consistently maintained a worldview, while others were self-conflicting. Analyzing stories generated by four models revealed a uniform narrative pattern, suggesting a lack of “state” necessary for fiction. The study highlights the limitations of current LLMs in fiction writing and advocates for future research to create story worlds for LLMs to reside in. The study uses various evaluation metrics, such as coherence and consistency, to assess the LLMs’ performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at whether big language models can write stories like humans do. The researchers asked nine of these models some questions and found that only two of them could keep a consistent idea of what was happening in their story. When they looked at the stories these models wrote, they saw that they were all very similar. This suggests that these models don’t really have a sense of what’s going on in their story, which is important for writing fiction. The study says we need to come up with new ways to help these models understand and create different worlds. |
