Finetuning Lightweight LLMs for Control Flow Graph Generation
The experimental results show that, through fine-tuning, lightweight LLMs achieve promising results for CFG generation, particularly when the input code is incomplete or erroneous, and cross-language generalization capability on programming language not included in the fine-tuning data is demonstrated.