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cs.CL2026
Do Language Models Know What Not to Say? Causal Evidence for Statistical Preemption in LLMs
Dongxin Guo, Jikun Wu, Siu Ming Yiu
How do learners acquire knowledge of what is unacceptable without negative evidence? Construction Grammar proposes statistical preemption: exposure to a conventional form (e.g., "d…
cs.CL2026
Sparse Autoencoders Map Brain-LLM Alignment onto Cortical Semantic Topography
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Intermediate layers of large language models (LLMs) best predict human brain responses to language, one of the most robust findings in computational neurolinguistics, yet why remai…
cs.CL2026
Brain-LLM Alignment Tracks Training Data, Not Typology
Dongxin Guo, Jikun Wu, Siu Ming Yiu
Brain-LLM alignment is well established in English, yet the brain's language network is neuroanatomically universal across languages. Does alignment also generalize cross-linguisti…