Summary of A Nurse Is Blue and Elephant Is Rugby: Cross Domain Alignment in Large Language Models Reveal Human-like Patterns, by Asaf Yehudai et al.
A Nurse is Blue and Elephant is Rugby: Cross Domain Alignment in Large Language Models Reveal Human-like Patterns
by Asaf Yehudai, Taelin Karidi, Gabriel Stanovsky, Ariel Goldstein, Omri Abend
First submitted to arxiv on: 23 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed study investigates how large language models (LLMs) conceptualize and reason about abstract concepts by adapting a cross-domain alignment task from cognitive science. The experiment prompts several LLMs with a mapping task, analyzing their responses at both the population and individual levels. Additionally, the paper evaluates the models’ ability to provide explanations for their mappings and assesses the similarity between human and model reasoning processes. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The study explores how large language models think about abstract concepts by asking them questions like “What color would a doctor be?” It looks at how different models respond to these questions and compares their answers to see if they’re similar. The researchers also looked at why the models gave certain answers, which shows that some models can provide good reasons for their choices, just like humans do. |
Keywords
» Artificial intelligence » Alignment
