Research
LLM4Decompile (EMNLP 2024)
Research on direct binary decompilation and refinement of Ghidra output with language models. Evaluates re-executability on HumanEval and ExeBench; useful for distinguishing readable output from functional recovery.
- Targets
- Binary
- Category
- Learning resources
- Relationship
- Learning resource
- Sources reviewed
Requirements & limits
- EMNLP 2024 paper. Results are author-reported for the evaluated models and benchmarks.
About this entry
The description was reviewed against primary sources.
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Primary sources
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