Summary of Multiple Choice Questions and Large Languages Models: a Case Study with Fictional Medical Data, by Maxime Griot et al.
Multiple Choice Questions and Large Languages Models: A Case Study with Fictional Medical Data
by Maxime Griot, Jean Vanderdonckt, Demet Yuksel, Coralie Hemptinne
First submitted to arxiv on: 4 Jun 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 This paper evaluates the effectiveness of multiple-choice questions (MCQs) in assessing the performance of Large Language Models (LLMs) like ChatGPT in a medical context. To isolate knowledge from test-taking abilities, the authors created a fictional benchmark focused on the non-existent Glianorex gland and developed corresponding MCQs in English and French. They evaluated various LLMs using these questions in a zero-shot setting, finding average scores around 67% with minor performance differences between models. Fine-tuned medical models showed some improvement over base versions in English but not in French. The results suggest that traditional MCQ-based benchmarks may not accurately measure LLMs’ clinical knowledge and reasoning abilities, instead highlighting their pattern recognition skills. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large Language Models like ChatGPT are getting good at helping with medical questions! But can they really understand what they’re talking about? This paper tries to figure out if the way we test them is working. They created a special set of fake medical questions and used them to test different models. The results show that the models are pretty good, but they might not be really understanding the answers – just recognizing patterns. This means we need to come up with better ways to test these models so we can know what they’re capable of. |
Keywords
» Artificial intelligence » Pattern recognition » Zero shot
