SwiftTrans improves both functional correctness and runtime efficiency of LLM code translations via multi-perspective exploration with hierarchical guidance and difference-aware selection with ordinal guidance on extended benchmarks including new SwiftBench.
Ecco: Can we improve model-generated code efficiency without sacrificing functional correctness?
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
ProgramBench introduces 200 tasks where models must reconstruct full programs like FFmpeg or SQLite from docs alone; none of 9 evaluated LMs fully solve any task and the best passes 95% tests on only 3% of tasks while favoring monolithic code.
PerfCoder is a family of LLMs trained on optimization trajectories with human annotations and runtime-based preference alignment that achieves higher runtime speedups and optimization rates on the PIE benchmark than prior models while producing interpretable feedback.
citing papers explorer
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Bridging Functional Correctness and Runtime Efficiency Gaps in LLM-Based Code Translation
SwiftTrans improves both functional correctness and runtime efficiency of LLM code translations via multi-perspective exploration with hierarchical guidance and difference-aware selection with ordinal guidance on extended benchmarks including new SwiftBench.
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ProgramBench: Can Language Models Rebuild Programs From Scratch?
ProgramBench introduces 200 tasks where models must reconstruct full programs like FFmpeg or SQLite from docs alone; none of 9 evaluated LMs fully solve any task and the best passes 95% tests on only 3% of tasks while favoring monolithic code.
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PerfCoder: Large Language Models for Interpretable Code Performance Optimization
PerfCoder is a family of LLMs trained on optimization trajectories with human annotations and runtime-based preference alignment that achieves higher runtime speedups and optimization rates on the PIE benchmark than prior models while producing interpretable feedback.