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Omer Moussa

2 accepted papers

2025

Brain-tuning Improves Generalizability and Efficiency of Brain Alignment in Speech Models

NeurIPS 2025poster

Pretrained language models are remarkably effective in aligning with human brain responses elicited by natural language stimuli, positioning them as promising model organisms for studying language processing in the brain. However, existing approaches for both estimating and improving this brain alig…

Cited by 0SourcecodeScholar
2025

Improving Semantic Understanding in Speech Language Models via Brain-tuning

ICLR 2025poster

Speech language models align with human brain responses to natural language to an impressive degree. However, current models rely heavily on low-level speech features, indicating they lack brain-relevant semantics which limits their utility as model organisms of semantic processing in the brain. In…