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Learn from Failure: Fine-Tuning LLMs with Trial-and-Error Data for Intuitionistic Propositional Logic Proving
Recent advances in Automated Theorem Proving have shown the effectiveness of leveraging a (large) language model that generates tactics (i. e. proof steps) to search through proof states.
Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development
When software developers modify one or more files in a large code base, they must also identify and update other related files.
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