mbzuai-oryx/Awesome-LLM-Post-training
A curated collection of papers, code implementations, benchmarks, and resources on LLM post-training methodologies for reasoning models.
Not currently ranked — collecting fresh signals.
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This repository aggregates the most influential works on post-training large language models, covering techniques like supervised fine-tuning, reinforcement learning from human feedback (RLHF), and reasoning enhancement. It serves as both a survey referenced by an arXiv paper and a practical guide for researchers and practitioners working on training and improving LLMs after pre-training.
Frequently asked
- What is mbzuai-oryx/Awesome-LLM-Post-training?
- A curated collection of papers, code implementations, benchmarks, and resources on LLM post-training methodologies for reasoning models.
- Is Awesome-LLM-Post-training open source?
- Yes — mbzuai-oryx/Awesome-LLM-Post-training is an open-source project tracked on heatdrop.
- What language is Awesome-LLM-Post-training written in?
- mbzuai-oryx/Awesome-LLM-Post-training is primarily written in Python.
- How popular is Awesome-LLM-Post-training?
- mbzuai-oryx/Awesome-LLM-Post-training has 2.5k stars on GitHub.
- Where can I find Awesome-LLM-Post-training?
- mbzuai-oryx/Awesome-LLM-Post-training is on GitHub at https://github.com/mbzuai-oryx/Awesome-LLM-Post-training.