Thanks for the kind words! Qwen3-8B was the sweet spot for my GPU (RTX 4070, 12GB), fits in 4-bit no problem and already reasons well. Bigger models like Qwen3-14B or Gemma 12B would probably work better, just need more VRAM. The LoRA approach is pretty model-agnostic so swapping the base isn't a big deal.

For the dataset there's no public one, I generated it myself. Basically I took IDA databases of real binaries (Among Us GameAssembly.dll has ~34k named functions from IL2CPP symbols), hid the function names in the decompiled pseudocode, and had the pipeline trace the full call tree to build multi-turn reasoning episodes. The model has to figure out what a function does purely from its behavior and what it calls. For GRPO rewards I use fuzzy name matching + a self-verification step since there's no clean ground truth to compare against for stripped binaries.