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HKUST-KnowComp/Awesome-LLM-Scientific-Discovery

Open source
Related Resources Updated Sep 16, 2026
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Compared with 10 other Related Resources agents Open source Self-hostable Updated Sep 2026
Open Source Updated Sep 2026 Self-hostable

Pricing

Open Source

Pricing not publicly listed.

Use cases

Surveying recent advancements in LLM-driven scientific discovery Identifying open-source tools for scientific NLP tasks Discovering benchmark datasets for evaluating LLMs in science Referencing foundational and cutting-edge research papers

Pros & cons

Pros

  • Comprehensive and well-organized resource repository
  • Focus on peer-reviewed and high-quality research
  • Open-source and freely accessible

Cons

  • Requires manual updates to stay current with new research
  • No direct tool integration—only references external resources
  • May lack depth in niche subfields due to broad scope

Overview

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.

Problem it solves

Provides a centralized, organized collection of research and tools for leveraging LLMs in scientific research, reducing the effort to find relevant materials.

Target audience: Developers and teams working with related resources automation.

Inputs

  • User configuration
  • API credentials (if required)
  • Task parameters

Outputs

  • Automated task results
  • Status reports
  • Generated content or actions

Example workflow

  1. 1 User configures the agent with required parameters
  2. 2 Agent receives input data or trigger
  3. 3 Agent processes the request using its core logic
  4. 4 Agent interacts with external services if needed
  5. 5 Results are returned to the user

Sample system prompt 


              You are HKUST-KnowComp/Awesome-LLM-Scientific-Discovery, an AI assistant. Help the user accomplish their task efficiently.

Tools & technologies

LLM APIs Python

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FAQs

What is 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.
How much does HKUST-KnowComp/Awesome-LLM-Scientific-Discovery cost?
HKUST-KnowComp/Awesome-LLM-Scientific-Discovery's pricing model is Open Source. Pricing not publicly listed.
What is HKUST-KnowComp/Awesome-LLM-Scientific-Discovery used for?
HKUST-KnowComp/Awesome-LLM-Scientific-Discovery is used for: Surveying recent advancements in LLM-driven scientific discovery; Identifying open-source tools for scientific NLP tasks; Discovering benchmark datasets for evaluating LLMs in science; Referencing foundational and cutting-edge research papers.
What are the best alternatives to HKUST-KnowComp/Awesome-LLM-Scientific-Discovery?
HKUST-KnowComp/Awesome-LLM-Scientific-Discovery is a Related Resources AI agent. Compare it with the best alternatives — ranked by features, pricing, and use case — on our HKUST-KnowComp/Awesome-LLM-Scientific-Discovery alternatives page.
Is HKUST-KnowComp/Awesome-LLM-Scientific-Discovery open source?
Yes, HKUST-KnowComp/Awesome-LLM-Scientific-Discovery is open source.
Can HKUST-KnowComp/Awesome-LLM-Scientific-Discovery be self-hosted?
Yes, HKUST-KnowComp/Awesome-LLM-Scientific-Discovery can be self-hosted.
What skill level is required to use HKUST-KnowComp/Awesome-LLM-Scientific-Discovery?
HKUST-KnowComp/Awesome-LLM-Scientific-Discovery is designed for intermediate users.

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