Tatsuki Kuribayashi

Idiom comprehension in low-resource languages suffers significantly, with literal meanings proving far more challenging than figurative interpretations, even in context-rich conversations.

Curriculum learning flips the script on what language structures LMs find "easy," suggesting that training order is a critical factor in shaping their inductive biases.

Fine-tuned neural language models can accurately predict human reading times for garden-path sentences, challenging the notion that surprisal cannot account for syntactic disambiguation.

Later layers of LLMs capture cognitive effort in syntactically challenging sentences better than earlier layers, but still miss the mark compared to human processing.