mbzuai-oryx/Awesome-LLM-Post-training resource

Health v2 · maintenance only

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2526 stars · 167 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A curated awesome-list and survey companion collecting papers, code, benchmarks, and resources on LLM post-training methodologies, organized into fine-tuning, reinforcement learning, and test-time scaling. It accompanies a TPAMI-accepted survey paper on reasoning large language models.

Use cases

• find papers on LLM post-training techniques
• learn about reasoning LLM methods like RLHF and test-time scaling
• survey fine-tuning and reinforcement learning approaches for LLMs
• find benchmarks for reasoning large language models
• keep up with new research on LLM reasoning
• prepare a literature review on post-training LLMs

When to choose

• you need a curated, taxonomy-organized reading list on LLM post-training
• you are researching reasoning models, RLHF, or test-time scaling
• you want the companion resources for the TPAMI/arXiv survey paper

When to avoid

• you need runnable training code or a production training framework
• you want a hands-on tutorial with step-by-step exercises rather than a paper list
• you need a maintained software library with releases

Facets

learning-resource · maturity active

llm-training machine-learning documentation large-language-models artificial-intelligence tutorials awesome-lists reinforcement-learning python post-training reasoning fine-tuning reinforcement-learning test-time-scaling survey curated-list rlhf

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markdown · JSON · MCP: product_card(name="mbzuai-oryx/Awesome-LLM-Post-training")