We introduce MADLAD-400, a manually audited, general domain 3T token
mon...
Natural language processing and 2D vision models have attained remarkabl...
We propose Neural Priming, a technique for adapting large pretrained mod...
Web-scale search systems learn an encoder to embed a given query which i...
Compositional representations of the world are a promising step towards
...
Learned representations are a central component in modern ML systems, se...
Recent advances have enabled automatic sound recognition systems for dea...
When data is publicly released for human consumption, it is unclear how ...
Learning binary representations of instances and classes is a classical
...
Enabling robust intelligence in the wild entails learning systems that o...
Pooling operators are key components in most Convolutional Neural Networ...
Sparsity in Deep Neural Networks (DNNs) is studied extensively with the ...
This paper introduces a new learning paradigm called eXtreme Regression ...
Edge sensing with micro-power pulse-Doppler radars is an emergent domain...
This paper develops the FastRNN and FastGRNN algorithms to address the t...