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2026 CoNLL CoNLL 2026

Readers make targeted regressions to plausible errors in reanalysis of “noisy-channel garden-path” sentences

AbstractA key question in psycholinguistics is how inferences about the meaning of linguistic input unfold incrementally a comprehender’s mind. In this work, we study reading dynamics for “noisy-channel garden-path” sentences, which temporarily appear well-formed but feature late-appearing violations of expectation that can be resolved not by inferring an alternative syntactic structure, but by inferring the presence of an error. We find evidence for targeted regressions – eye movements towards regions that are promising loci of possible errors in light of later-arriving information, showing patterns consistent with the posterior inferences of a model of noisy-channel processing with reanalysis. We discuss the implications of these findings for theories of noisy-channel language comprehension and information-theoretic explanations of reading dynamics.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Interdisciplinary

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