YangLing0818/SuperCorrect-llm

[ICLR 2025] SuperCorrect: Advancing Small LLM Reasoning with Thought Template Distillation and Self-Correction

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Experimental

This project helps developers improve the reasoning and self-correction abilities of smaller Large Language Models (LLMs). It takes a standard LLM as input and, through a specialized fine-tuning process, outputs a more accurate and robust LLM capable of complex problem-solving. This is primarily for AI/ML developers and researchers who are building or fine-tuning LLMs for advanced reasoning tasks.

No commits in the last 6 months.

Use this if you are a developer or researcher looking to significantly enhance the mathematical and logical reasoning capabilities of your smaller LLMs, making them more competitive with larger models.

Not ideal if you are a non-technical end-user simply looking for an off-the-shelf powerful AI model for general use, as this project requires deep technical expertise to implement.

LLM development AI model training reasoning AI machine learning research model fine-tuning
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 8 / 25
Community 10 / 25

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87

Forks

7

Language

Python

License

Last pushed

Mar 23, 2025

Commits (30d)

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