Summary of Are Llms Good Cryptic Crossword Solvers?, by Abdelrahman Sadallah et al.
Are LLMs Good Cryptic Crossword Solvers?
by Abdelrahman Sadallah, Daria Kotova, Ekaterina Kochmar
First submitted to arxiv on: 15 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); 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 paper explores the capabilities of large language models (LLMs) in solving cryptic crosswords, a puzzle that requires manipulating language at different levels and dealing with various wordplay. Previous research indicates that even modern NLP models struggle with this task, leaving it unclear how well LLMs would perform. The authors investigate three popular LLMs, LLaMA2, Mistral, and ChatGPT, comparing their performance to human solvers. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Cryptic crosswords are puzzles that need solving skills and language manipulation abilities. Big language models aren’t good at this yet. This paper looks at how well these models do on this task compared to humans. |
Keywords
* Artificial intelligence * Nlp
