Papers with refinement approach

1 papers
LLM4Decompile: Decompiling Binary Code with Large Language Models (2024.emnlp-main)

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Challenge: Decompilation aims to convert binary code to high-level source code, but traditional tools like Ghidra often produce results that are difficult to read and execute.
Approach: They propose an open-source LLM series trained to decompile binary code . they optimize the LLM training process and introduce the Llm4Decompile-End models .
Outcome: The proposed models outperform GPT-4o and Ghidra on the HumanEval and ExeBench benchmarks by over 100% in terms of re-executability rate.

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