14 citations · 19 across the 4 of their papers we have counts for
4 papers
Revealing Vision-Language Integration in the Brain with Multimodal Networks
Vighnesh Subramaniam, Colin Conwell, Christopher Wang +4
We use (multi)modal deep neural networks (DNNs) to probe for sites of multimodal integration in the human brain by predicting stereoencephalography (SEEG) recordings taken while hu…
SecureLLM: Using Compositionality to Build Provably Secure Language Models for Private, Sensitive, and Secret Data
Abdulrahman Alabdulkareem, Christian M Arnold, Yerim Lee +3
Traditional security mechanisms isolate resources from users who should not access them. We reflect the compositional nature of such security mechanisms back into the structure of…
BrainBERT: Self-supervised representation learning for intracranial recordings
Christopher Wang, Vighnesh Subramaniam, Adam Uri Yaari +4
We create a reusable Transformer, BrainBERT, for intracranial recordings bringing modern representation learning approaches to neuroscience. Much like in NLP and speech recognition…
Developing a Series of AI Challenges for the United States Department of the Air Force
Vijay Gadepally, Gregory Angelides, Andrei Barbu +39
Through a series of federal initiatives and orders, the U.S. Government has been making a concerted effort to ensure American leadership in AI. These broad strategy documents have…