Given a codebase and an issue, a language model is tasked with generating a patch that resolves the described problem.
Given a codebase and an issue, a language model is tasked with generating a patch that resolves the described problem.
github.com GitHub - princeton-nlp/SWE-bench: [ICLR 2024] SWE-Bench: Can Language Models Resolve Real-world Github Issues?
[ICLR 2024] SWE-Bench: Can Language Models Resolve Real-world Github Issues? - princeton-nlp/SWE-bench
![GitHub - princeton-nlp/SWE-bench: [ICLR 2024] SWE-Bench: Can Language Models Resolve Real-world Github Issues?](https://lemmy.ml/pictrs/image/c21def42-72d6-49a0-9f2c-dfa5d5472501.png?format=webp&thumbnail=256)
You can call it self healing
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