HKUST-KnowComp/Awesome-LLM-Scientific-Discovery vs openags/Awesome-AI-Scientist-Papers
A side-by-side comparison of two Related Resources AI agents - to help you pick the right one.
HKUST-KnowComp/Awesome-LLM-Scientific-Discovery
HKUST-KnowComp/Awesome-LLM-Scientific-Discovery is a curated GitHub repository compiling resources, tools, and research papers on the application of large language models (LLMs) in scientific discovery. It serves as a reference hub for researchers and practitioners exploring LLMs in scientific contexts, including survey papers like the EMNLP 2025 submission.
openags/Awesome-AI-Scientist-Papers
openags/Awesome-AI-Scientist-Papers is a curated collection of academic papers and research focused on AI scientists and robot scientists. It serves as a centralized resource for accessing key publications in this niche field.
Feature comparison
| HKUST-KnowComp/Awesome-LLM-Scientific-Discovery | openags/Awesome-AI-Scientist-Papers | |
|---|---|---|
| Category | Related Resources | Related Resources |
| Open source | ||
| Self-hostable | ||
| Skill level | Intermediate | Intermediate |
| Pricing | Open Source | Open Source |
HKUST-KnowComp/Awesome-LLM-Scientific-Discovery: what it solves
Provides a centralized, organized collection of research and tools for leveraging LLMs in scientific research, reducing the effort to find relevant materials.
openags/Awesome-AI-Scientist-Papers: what it solves
It aggregates and organizes scattered research papers on AI and robot scientists, saving researchers time in finding relevant literature.