@DanKornas: Reading LLM research gets slow when every topic starts with another search. Awesome-LLM-Survey is a topic-organized col…
Summary
Awesome-LLM-Survey is a topic-organized GitHub repository collecting LLM survey papers and project links to help researchers quickly find overviews across training, prompting, modalities, and applications.
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Cached at: 07/22/26, 02:30 PM
Reading LLM research gets slow when every topic starts with another search.
Awesome-LLM-Survey is a topic-organized collection of LLM survey papers for researchers and builders mapping the field.
It helps you find useful overviews faster by grouping paper links—and, where provided, related project links—under a detailed README index.
Key features:
• Training and alignment – sections cover instruction tuning and human alignment. • Prompting and retrieval – browse chain-of-thought, prompt engineering, and RAG surveys. • Model challenges – trace work on hallucination, evaluation, reasoning, explainability, security, privacy, and more. • Modalities and domains – explore visual, audio, and code LLMs alongside health, finance, education, law, and robotics. • Downstream applications – jump into recommendation, information retrieval, software engineering, autonomous driving, time series, and other task areas.
Free public GitHub repo.
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