chore: upload paper to the repo

[garrett4wade]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @garrett4wade, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request centralizes the hosting of research papers by integrating them directly into the repository. This change ensures that the associated documentation consistently references these local copies, enhancing accessibility and long-term availability of the papers alongside the codebase.

Highlights

• Paper Upload: The research paper related to ASearcher and AReaL v0.3 has been uploaded directly to the repository, making it locally accessible.
• README Update: The README.md file has been updated to replace external arXiv links for the ASearcher and AReaL v0.3 papers with internal links pointing to the newly uploaded assets/paper.pdf.

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[gemini-code-assist]

Code Review

This pull request aims to add the project's research paper to the repository and update links in the README.md. However, in doing so, it seems to have incorrectly replaced a link to a different paper (for the ASearcher project) with the main AReaL paper. I've added a comment to address this. Additionally, for consistency, you might consider updating other links to the paper within the repository, such as the one in docs/algorithms/async.md.

[gemini-code-assist]

This change incorrectly points the ASearcher paper link to assets/paper.pdf. The original link was for the ASearcher paper (arXiv:2508.07976), while assets/paper.pdf appears to be the main AReaL paper (arXiv:2505.24298), which is correctly updated later in this file. Since these are two different papers, this link should likely be reverted to its original target.

Suggested change

	AReaL's end-to-end asynchronous RL training. Check out the [paper](assets/paper.pdf) and
	the [open-source repository](https://github.com/inclusionAI/ASearcher)!
	AReaL's end-to-end asynchronous RL training. Check out the [paper](https://arxiv.org/pdf/2508.07976) and
	the [open-source repository](https://github.com/inclusionAI/ASearcher)!