Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Large language models (LLMs) have come closest among all models to date to mastering
human language, yet opinions about their linguistic and cognitive capabilities remain split …

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 …

Large-scale task planning is a major challenge. Recent work exploits large language
models (LLMs) directly as a policy and shows surprisingly interesting results. This paper …

We argue that auto-regressive LLMs cannot, by themselves, do planning or self-verification
(which is after all a form of reasoning), and shed some light on the reasons for …

Instruction-following models are attractive alternatives to fine-tuned approaches for question
answering (QA). By simply prepending relevant documents and an instruction to their input …

Generative artificial intelligence (AI) has the potential to revolutionize research. I analyze
how large language models (LLMs) such as ChatGPT can assist economists by describing …

This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …

The widespread adoption of large language models (LLMs) makes it important to recognize
their strengths and limitations. We argue that in order to develop a holistic understanding of …

Large language models exhibit surprising emergent generalization properties, yet also
struggle on many simple reasoning tasks such as arithmetic and parity. This raises the …