rStar-RL/LoongRL

LoongRL: Reinforcement Learning for Advanced Reasoning over Long Contexts (ICLR 2026 Oral)

20
/ 100
Experimental

This project helps large language models (LLMs) understand and answer questions from very long texts, and solve complex math problems more effectively. It takes in existing LLMs and training data to produce models that can reason better over extensive documents or complex mathematical challenges. Scientists, data engineers, or machine learning researchers who work with advanced LLM development would use this.

Use this if you need to train or fine-tune large language models to excel at understanding information spread across very long documents or to solve advanced mathematical reasoning tasks with high accuracy.

Not ideal if you are looking for an out-of-the-box LLM application or if your primary need is for basic, short-context text generation rather than deep reasoning over long inputs.

large-language-models long-context-reasoning mathematical-reasoning model-fine-tuning AI-development
No License No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 5 / 25
Community 0 / 25

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13

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Language

Python

License

Last pushed

Feb 20, 2026

Commits (30d)

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