Build-bench is the first architecture-aware benchmark that evaluates LLMs on repairing cross-ISA build failures via iterative tool-augmented reasoning, with the best model reaching 63.19% success.
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EvidenT repairs 53.88% of real-world RISC-V system-level package build failures by preserving repair history and build artifacts in a closed-loop validation system, outperforming baselines by a wide margin.
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Can Language Models Go Beyond Coding? Assessing the Capability of Language Models to Build Real-World Systems
Build-bench is the first architecture-aware benchmark that evaluates LLMs on repairing cross-ISA build failures via iterative tool-augmented reasoning, with the best model reaching 63.19% success.
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EvidenT: An Evidence-Preserving Framework for Iterative System-Level Package Repair
EvidenT repairs 53.88% of real-world RISC-V system-level package build failures by preserving repair history and build artifacts in a closed-loop validation system, outperforming baselines by a wide margin.