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vectorspacelab/agentswe — Hugging Face Papers link added

The latest commit in vectorspacelab/agentswe added a Hugging Face Papers badge and a news line link next to the arXiv (2610.13361) badge in the README and the Chinese README.

Repositoryvectorspacelab/agentswe ↗

The latest commit in vectorspacelab/agentswe added a Hugging Face Papers badge and a news line link next to the arXiv (2610.13361) badge in the README and the Chinese README.

GitHub description: Can coding agents build the agent you actually want? A benchmark of 25 agent software engineering tasks across creation, editing and optimization.

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Language
Python
License
Apache-2.0
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The latest commit in vectorspacelab/agentswe is 6643c73, recorded at 2026-10-13 04:51 UTC, and the only changed files are README.md and the Chinese version README_zh.md. The content is one more Hugging Face Papers badge placed next to the arXiv (2610.13361) badge, and the sentence in the news line that said the paper is only on arXiv expanded to both arXiv and Hugging Face Papers. The change is 6 lines (4 added, 2 removed).

AgentSWE is a benchmark that measures whether coding agents can actually create the agent they want. According to the repository description, it has a total of 25 software engineering tasks spread across three stages: Creation, Editing, and Optimization, and the README lists 10 creation and 10 editing tasks. The structure is to submit an agent and then test it again by attaching use cases that the agent has not seen, and the 2026-10 news entry mentions the code, the 25 tasks, and the release of the Lite set together. The license badge is Apache-2.0, and the project page and paper links were already in place before this commit.

The effect of this change is closer to the access path than to the output. The paper number 2610.13361 is unchanged; the README merely announces that the same paper page has also opened on Hugging Face Papers. The only files containing output are the two READMEs, and results such as evaluation scores or model rankings do not appear in the changed portions. The number of tasks in the optimization stage and the size of the Lite set cannot be confirmed from this commit alone. The commit message still contains a co-authorship credit for Claude Opus 5.5. What conclusions the benchmark reaches can only be known by directly checking the original paper and the published 25 tasks, so this commit is best read as a documentation change that adds one more route to the paper.