47 citations · 48 across the 3 of their papers we have counts for
3 papers
Neuro2Semantic: A Transfer Learning Framework for Semantic Reconstruction of Continuous Language from Human Intracranial EEG
Siavash Shams, Richard Antonello, Gavin Mischler +3
Decoding continuous language from neural signals remains a significant challenge in the intersection of neuroscience and artificial intelligence. We introduce Neuro2Semantic, a nov…
AAD-LLM: Neural Attention-Driven Auditory Scene Understanding
Xilin Jiang, Sukru Samet Dindar, Vishal Choudhari +6
Auditory foundation models, including auditory large language models (LLMs), process all sound inputs equally, independent of listener perception. However, human auditory perceptio…
Contextual Feature Extraction Hierarchies Converge in Large Language Models and the Brain
Gavin Mischler, Yinghao Aaron Li, Stephan Bickel +2
Recent advancements in artificial intelligence have sparked interest in the parallels between large language models (LLMs) and human neural processing, particularly in language com…