Papers with conversational problem

    1 papers
    SWE-Dev: Building Software Engineering Agents with Training and Inference Scaling (2025.findings-acl)

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    Challenge: Large language models (LLMs) have advanced rapidly from conversational problem solving to addressing real-world tasks involving tool use, such as software engineering (SWE).
    Approach: They propose to build an LLM-based software engineering agent that synthesizes test cases and scales up agent trajectories to build training data.
    Outcome: The proposed model outperforms state-of-the-art models on the SWE-bench-Verified benchmark.

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