Perturbation method traces linguistic representations in language models

A newly revised arXiv paper proposes a perturbation-based technique for locating and evaluating linguistic representations inside deep neural language models, framing it as an adversarial tracer. The authors note that representation discovery remains unresolved, and that loosely constrained alignment procedures can make the very notion of a representation vacuous. Their approach aims to provide a simpler and more efficient way to probe how such models encode language.