Summary of The Impossible Test: a 2024 Unsolvable Dataset and a Chance For An Agi Quiz, by David Noever et al.
The Impossible Test: A 2024 Unsolvable Dataset and A Chance for an AGI Quiz
by David Noever, Forrest McKee
First submitted to arxiv on: 20 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 A novel evaluation framework is introduced to assess large language models’ (LLMs) ability to acknowledge uncertainty on 675 fundamentally unsolvable problems. A curated dataset of graduate-level grand challenge questions with intentionally unknowable answers is used to evaluate twelve state-of-the-art LLMs, including both open and closed-source models, on their propensity to admit ignorance rather than generate plausible but incorrect responses. The best models scored in 62-68% accuracy ranges for admitting the problem solution was unknown in fields ranging from biology to philosophy and mathematics. An inverse relationship between problem difficulty and model accuracy is observed, with GPT-4 demonstrating higher rates of uncertainty acknowledgment on more challenging problems (35.8%) compared to simpler ones (20.0%). This pattern indicates that models may be more prone to generate speculative answers when problems appear more tractable. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research introduces a way to test how well large language models understand when they don’t know the answer. The test asks 12 of these models to solve tricky questions with no clear answers, like “What is the meaning of life?” or “How do plants grow in space?” Most models did okay, admitting that they didn’t know the answers to about 40% of the questions. But some models were better at recognizing when they didn’t know something than others. |
Keywords
» Artificial intelligence » Gpt
