Clinical decision-making is one of the most impactful parts of a physician's responsibilities
and stands to benefit greatly from artificial intelligence solutions and large language models …

We introduce ChatPose a framework employing Large Language Models (LLMs) to
understand and reason about 3D human poses from images or textual descriptions. Our …

In an era where symbolic mathematical equations are indispensable for modeling complex
natural phenomena, scientific inquiry often involves collecting observations and translating …

The poor performance of transformers on arithmetic tasks seems to stem in large part from
their inability to keep track of the exact position of each digit inside of a large span of digits …

In this work we introduce Labrador, a pre-trained Transformer model for laboratory data.
Labrador and BERT were pre-trained on a corpus of 100 million lab test results from …

The integration of Large Language Models (LLMs) into the drug discovery and development
field marks a significant paradigm shift, offering novel methodologies for understanding …

Effectively representing materials as text has the potential to leverage the vast
advancements of large language models (LLMs) for discovering new materials. While LLMs …

Language models (LMs) are bound to their tokenizer, which maps raw text to a sequence of
vocabulary items (tokens). This restricts their flexibility: for example, LMs trained primarily on …

Data-driven simulation surrogates help computational scientists study complex systems.
They can also help inform impactful policy decisions. We introduce a learning framework for …

This book is a self-contained introduction to the design of modern (deep) neural networks.
Because the term" neural" comes with a lot of historical baggage, I prefer the simpler term" …