sileod/reasoning_core

Procedural symbolic reasoning data generators suite for synthetic pretraining

39
/ 100
Emerging

This tool helps AI researchers and developers create synthetic datasets for training and evaluating large language models (LLMs). It generates textual examples of complex symbolic and algorithmic reasoning tasks, such as formal logic, mathematics, and planning problems. You can use these generated datasets to improve an LLM's ability to handle intricate reasoning challenges.

Use this if you need to generate large, diverse datasets of symbolic reasoning tasks to pre-train or fine-tune language models.

Not ideal if you are looking for real-world, natural language datasets or if your project doesn't involve training language models on formal reasoning tasks.

AI-research language-model-training synthetic-data-generation reasoning-evaluation computational-logic
No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 6 / 25

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Stars

34

Forks

2

Language

Python

License

MIT

Last pushed

Mar 12, 2026

Commits (30d)

0

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