This repository serves as a collaborative, open-source effort to systematically organize and track the rapidly expanding literature on Large Language Models (LLMs) and autonomous agents in scientific discovery, particularly chemistry. It aims to provide a structured overview of trends, challenges, and potential applications for researchers and practitioners in AI and scientific domains.

How It Works

The project functions as a curated database and discussion platform for scientific papers related to LLMs and autonomous agents. It categorizes research into key areas such as LLM models, LLM-based autonomous agents (including memory, planning, tools, and perception modules), and their applications within specific scientific fields like chemistry. The goal is to maintain an up-to-date, community-driven resource to counter the fast-paced nature of AI research.

Highlighted Details

• Focuses on LLMs and autonomous agents within scientific discovery, with an emphasis on chemistry.
• Aims to provide a structured overview of trends, challenges, and potential applications.
• Designed as an open-source, collaborative environment for organizing a large volume of daily publications.

Maintenance & Community

The project encourages community contributions to maintain its systematic structure and keep pace with the rapid advancements in the field. Details on how to contribute are available in the CONTRIBUTING.md file.

Licensing & Compatibility

The repository's licensing is not specified in the provided README. Users should verify licensing details before commercial use or integration into closed-source projects.

Limitations & Caveats

The README explicitly states that the review paper is not exhaustive and will become outdated quickly due to the rapid pace of AI research. The repository's primary function is to serve as a dynamic, community-maintained resource rather than a static, definitive review.