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Pretraining data, not verifiability, is why LLMs are especially good at math (and coding)
LLMs excel at math and coding primarily because their pretraining data in these fields is uniquely high-quality and reliable.
What: Steven Byrnes argues that LLMs are not inherently better at verifying math than other subjects, but rather that math and coding literature contains significantly less "confused nonsense" than fields like psychology, allowing imitative learning to produce higher-quality outputs.
Why it matters: This challenges the popular view that LLM math capabilities are driven primarily by verifiability or RL-in-the-loop, suggesting that data quality acts as a bottleneck for generalization in less rigorous fields.
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