Generative AI for Math (OpenWebMath / MathPile)
Free while signed in. Answers cite the passages they came from.

Releases a diverse, high-quality math-centric corpus of ~9.5B tokens designed for training math-capable foundation models.
9.5B-token corpus: Curated from mathematical content across the web, textbooks, papers, and Q&A, rebalanced for math-specific token distribution.
Quality filtering: Applies math-specific filtering to surface content dense in symbolic notation, proofs, and problem solutions rather than surface-level mentions of math.
Diverse sources: Explicitly mixes proof-heavy formal math with applied problem-solving to avoid over-fitting to any single mathematical register.
Training signal: Positioned as a drop-in pretraining or continual-pretraining corpus to lift math reasoning in existing LLMs without changing the architecture.
Get next week’s papers.
The same picks and the same summaries, in your inbox. Free, and 176 issues deep.
Subscribe on Substack