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The Illusion of Replacement: Rethinking Specialized Machine Learning Models in the Foundation Model Era

arXiv · AI, language, vision and robotics · article · Aug 29, 2026 · UTC

Can the specialized architectures that machine learning has traditionally built for structured data be replaced by language-based models? This question is examined through a review of 159 papers (2016--2026) across nine modalities, with predictive accuracy considered alongside structural representation and computation. A distinction is made between performing a task and preserving and computing the structure that makes the task tractable, and existing approaches are organized into eight representational regimes, ranging from language-only systems to fully specialized architectures. Language-me

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