Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

This paper embarks on an exploration into the Large Language Model (LLM) datasets,
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …

Ever since the Turing Test was proposed in the 1950s, humans have explored the mastering
of language intelligence by machine. Language is essentially a complex, intricate system of …

We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and
reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is …

In this work we explore recent advances in instruction-tuning language models on a range of
open instruction-following datasets. Despite recent claims that open models can be on par …

Large language models (LLMs) have demonstrated impressive capabilities, but the bar for
clinical applications is high. Attempts to assess the clinical knowledge of models typically …

Large language models (LLMs) have demonstrated impressive capabilities in natural
language understanding and generation, but the quality bar for medical and clinical …

Finetuning language models on a collection of datasets phrased as instructions has been
shown to improve model performance and generalization to unseen tasks. In this paper we …

Text embeddings are commonly evaluated on a small set of datasets from a single task not
covering their possible applications to other tasks. It is unclear whether state-of-the-art …

Effective scaling and a flexible task interface enable large language models to excel at many
tasks. We present PaLI (Pathways Language and Image model), a model that extends this …