ylfeng/ReF-Decompile-lora

ReF Decompile

This model is a fine-tuned version of LLM4Binary/llm4decompile-6.7b-v1.5.

Results

Model/Metrics	Re-executability Rate (%)					Readability (#)
	O0	O1	O2	O3	AVG	O0	O1	O2	O3	AVG
Rule Based Decompiler
ghidra	34.76	16.46	15.24	14.02	20.12	2.98	2.41	2.52	2.38	2.57
Refine-Based Method
GPT-4o	46.95	34.15	28.66	31.10	35.22	2.82	2.35	2.29	2.31	2.44
LLM4Decompile-Ref	74.39	46.95	47.56	42.07	52.74	4.08	3.38	3.34	3.19	3.50
End-to-End Method
LLM4Decompile-End	69.51	44.51	39.63	38.41	48.02	4.07	3.46	3.40	3.23	3.54
FAE Decompile	67.68	48.78	45.73	42.07	51.07	3.94	3.46	3.40	3.25	3.51
FAE Decompile+SCC	70.24	48.54	47.56	43.29	52.41	3.97	3.48	3.41	3.23	3.52
ReF Decompile	85.37	56.10	51.83	52.43	61.43	4.13	3.60	3.54	3.49	3.69

Resources

• Code
• Model
• Paper