Abstract Our goal is to use AI to automatically find tax minimization strategies, an approach which we call “Shelter Check.” It would come in two variants. Existing-Authority Shelter Check would aim to find whether existing[...]

Abstract Large-scale generative models such as GPT and DALL-E have revolutionized natural language processing and computer vision research. These models not only generate high fidelity text or image outputs, but also demonstrate impressive domain and[...]

Abstract Pretrained language models (LMs) encode implicit representations of knowledge in their parameters. Despite this observation, our best methods for interpreting these representations yield few actionable insights on how to manipulate this parameter space for[...]

 

 

Abstract Recent advances in speech technology make heavy use of pre-trained models that learn from large quantities of raw (untranscribed) speech, using “self-supervised” (ie unsupervised) learning. These models learn to transform the acoustic input into[...]