LATIDIA · Investigación

Descomposición de la alineación cerebro-LLM con representaciones semánticas interpretables

arXiv: 2610.21508v1Tipo de anuncio: nuevo Resumen: Los modelos de lenguaje grande (LLM) predicen respuestas neuronales durante la comprensión del lenguaje naturalista, pero la información lingüística subyacente a esta alineación cerebral sigue siendo diferente

La noticia

arXiv:2610.21508v1 Announce Type: new Abstract: Large language models (LLMs) predict neural responses during naturalistic language comprehension, but the linguistic information underlying this brain alignment remains difficult to interpret. We use SCRIBE, an interpretable contextual semantic representation spanning 65 neurocognitively grounded semantic properties, as a lens for decomposing the brain alignment of one LLM, LLaMA2-7B. Using variance partitioning between LLaMA2-7B and SCRIBE on naturalistic fMRI data from seven participants listening to narrative stories (Moth Radio Hour), we separate brain-predictive variance shared between the two representations from variance unique to each. We find that shared variance is the dominant component across the whole brain and language-related regions, while both representations also retain