Introduces the binning semiring and causal graphical models to show that correlational evaluation of learnability in formal language tasks leads to incorrect conclusions from confounders.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) , month=
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A unified algebraic account reduces RNN expressivity to syntactic monoid division in wreath products and shows diagonal state-space models realize every even-modulus counter under unsigned-integer quantization but none under floating-point recurrences.
citing papers explorer
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Causally Evaluating the Learnability of Formal Language Tasks
Introduces the binning semiring and causal graphical models to show that correlational evaluation of learnability in formal language tasks leads to incorrect conclusions from confounders.
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An Algebraic View of the Expressivity of Recurrent Language Models
A unified algebraic account reduces RNN expressivity to syntactic monoid division in wreath products and shows diagonal state-space models realize every even-modulus counter under unsigned-integer quantization but none under floating-point recurrences.