Language Models Learn Shortcuts Instead of True Reasoning, Study Shows

This is a Plain English Papers summary of a research paper called Language Models Learn Shortcuts Instead of True Reasoning, Study Shows. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Overview

• Research investigates why implicit reasoning fails to match explicit step-by-step reasoning in language models
• Study trained GPT-2 models on mathematical reasoning tasks to analyze reasoning abilities
• Found language models can perform implicit reasoning well, but only on fixed patterns
• Models struggle to generalize implicit reasoning to new patterns
• Even state-of-the-art large language models (LLMs) show this limitation
• Suggests models learn reasoning "shortcuts" rather than true reasoning capabilities

Plain English Explanation

Think about how you might solve a complex math problem. You could write out each step carefully (explicit reasoning), or you might just jump to the answer after thinking about it mentally (implicit reasoning).

Large language models like GPT-4 and Claude are getting better at e...

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