reading time

An Existence Proof for Neural Language Models That Can Explain Garden-Path Effects via Surprisal ACL 2026 Cognitive Signatures of Multi-Word Expressions: Reading-Time and Surprisal EACL 2026 Eye Movement Features Can Predict Human Preferences on Machine-Generated Texts ACL 2026 Information-Theoretic Storage Cost in Sentence Comprehension CoNLL 2026 On the scaling relationship between cloze probabilities and language model next-token prediction CoNLL 2026 Probing for Reading Times ACL 2026 Syntactically-guided Information Maintenance in Sentence Comprehension CoNLL 2026 Word predictability estimates from language models are not robust to tokenizer vocabulary CoNLL 2026 Are Larger Language Models Better at Disambiguation? NAACL 2025 Exploring the Effect of Nominal Compound Structure in Scientific Texts on Reading Times of Experts and Novices ACL 2025 How Well Does First-Token Entropy Approximate Word Entropy as a Psycholinguistic Predictor? IJCNLP 2025 Investigating Psychometric Predictive Power of Syntactic Attention CoNLL 2025 Linear Recency Bias During Training Improves Transformers’ Fit to Reading Times COLING 2025 Modeling Bottom-up Information Quality during Language Processing EMNLP 2025 The Impact of Token Granularity on the Predictive Power of Language Model Surprisal ACL 2025 The Inverse Scaling Effect of Pre-Trained Language Model Surprisal Is Not Due to Data Leakage ACL 2025 Transformers Can Model Human Hyperprediction in Buzzer Quiz NAACL 2025 Do large language models and humans have similar behaviours in causal inference with script knowledge? NAACL 2024 Language models emulate certain cognitive profiles: An investigation of how predictability measures interact with individual differences ACL 2024 Modeling Nonnative Sentence Processing with L2 Language Models EMNLP 2024 Reverse-Engineering the Reader EMNLP 2024 Temperature-scaling surprisal estimates improve fit to human reading times – but does it do so for the “right reasons”? ACL 2024 The Effect of Surprisal on Reading Times in Information Seeking and Repeated Reading CoNLL 2024 Towards a Similarity-adjusted Surprisal Theory EMNLP 2024 Analyzing Cognitive Plausibility of Subword Tokenization EMNLP 2023