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N2NMatcher achieves remarkable improvements in binary code similarity analysis by effectively countering the disruptive effects of function inlining.
LLMs possess a "word recovery" mechanism that allows them to reconstruct canonical word-level tokens from character-level inputs, explaining their surprising robustness to non-canonical tokenization.
