Post-Hoc Attention Steering of Large Language Models for Robust Code Understanding under Obfuscation
This work proposes CodeSteer, a novel attention steering approach that reallocates model attention toward semantically relevant program elements, including backward slices for output prediction and control-flow paths for execution reasoning in large language models.