Unverified50% confidenceFactExact time
The surprisal of monolingual language models has been repeatedly validated as an effective predictor of native speakers' reading times.
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Long-term
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10/23/2026
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UnverifiedThis work is in the same vein as Paleka et al.'s "Consistency Checks for Language Model Forecasters."79% similarUnverifiedThe predictions of feature-based traditional readability models can be traced back to specific linguistic properties, giving them an interpretability advantage.74% similarUnverifiedWhen a bilingual model's training L1 matches the reader's native language, its predictions of L2 reading times are more accurate than the monolingual baseline and the mismatched group.71% similarUnverifiedThe study provides behavioral-level evidence that "bilingual models capture some aspects of cross-linguistic influence."69% similarUnverifiedCurrent mainstream large language models are essentially performing text prediction, calculating the most likely next word based on existing context, with no understanding, intent, or consciousness.68% similar
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