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cs.CL2026
Off-Axis, On Purpose: Where a Transformer Computes Concepts and Why it Does So
Mark Oskin
A transformer's answer lives on one axis: the direction its unembedding reads. Its intermediate states largely do not, and that off-axis position is usually treated as an obstacle…
cs.CL2026
Legible-by-Construction: Attention and End-to-End Transformers
Mark Oskin
A companion paper showed that a transformer's feed-forward layer can be rebuilt from explicit fuzzy set operations - intersection, set-difference, and a self-forgetting sequence qu…
cs.CL2026
Explicit Fuzzy Logic in the Feed-Forward Layer: Self-Forgetting Quantifiers Discover Legible Grammatical-Licensing Detectors
Mark Oskin
A transformer's feed-forward (FFN) sublayer materializes the distinctions attention gathers, yet gives no account of what it computes. In a parameter-neutral replacement, each hidd…