Kristina Toutanova

Co-authored BERT: a turning point for transfer learning in NLP.

A core name in the pretraining era of NLP, especially if you want to understand how BERT reshaped the field and how that line of work extended into broader document understanding and large-scale language systems.

One of the most important architecture-level thinkers in modern AI, with influence spanning Transformers, efficient scaling, and mixture-of-experts systems.

A foundational figure in modern sequence modeling whose work on the Transformer changed the technical direction of language and multimodal systems.

A foundational transformer co-author who is now worth following for a very different reason: he is one of the few people trying to build a serious frontier lab around alternatives to the default scaling path.

A foundational transformer researcher whose work still matters because it connects the original architecture shift to later efforts on efficiency, scaling, and sequence modeling infrastructure.