Decoding Stumpers: Large Language Models vs. Human Problem-Solvers (2023.findings-emnlp)
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| Challenge: | Recent advances in large language models have led to the development of systems 2 models that can solve complex tasks and predict human behavior. |
| Approach: | They compare the performance of four state-of-the-art LLMs to human participants and compare their results to stumpers, a unique single-step intuition problem that humans can easily verify. |
| Outcome: | The proposed models excel in solving stumpers and surpass human performance on stumpers, while humans exhibit superior skills in verifying solutions to the same problems. |
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