3 papers
cs.CL2026
Fine-tuning language encoding models on slow fMRI improves prediction for fast ECoG
Aditya R. Vaidya, Richard J. Antonello, Alexander G. Huth
Neuroscientists have recently turned to intracranial brain recording methods, like electrocorticography (ECoG), for human experiments because of the fine spatial and temporal resol…
cs.CL2026
Abstraction Induces the Brain Alignment of Language and Speech Models
Emily Cheng, Aditya R. Vaidya, Richard Antonello
Research has repeatedly demonstrated that intermediate hidden states extracted from large language models and speech audio models predict measured brain response to natural languag…
cs.CL2025
BrainWavLM: Fine-tuning Speech Representations with Brain Responses to Language
Nishitha Vattikonda, Aditya R. Vaidya, Richard J. Antonello +1
Speech encoding models use auditory representations to predict how the human brain responds to spoken language stimuli. Most performant encoding models linearly map the hidden stat…