Cognitive Expert Language Models Better Align with the Corresponding Brain Systems
Large language models (LLMs) can predict human brain activity across a variety of brain regions during natural language comprehension. Typically, however, LLM-brain alignment is measured using one model for different regions of the brain, and then model performance is summarized across regions. This one-model-fits-all approach ignores the functional specialization of brain regions. In this study, we assess whether a model oriented toward a particular cognitive domain aligns better with the brain system dedicated to that domain. Through prompting and fine-tuning, we first build expert LLM variants for six domains: sensory, spatial, numerical, reasoning, social, and abstract processing. We ...
| Authors | Zhivar Sourati, Mengxuan Helen Wu, Nona Ghazizadeh et al. |
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| Primary category | cs.CL |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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