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 …

Research on prompting has shown excellent performance with little or even no supervised
training across many tasks. However, prompting for machine translation is still under …

Multitask prompted finetuning (MTF) has been shown to help large language models
generalize to new tasks in a zero-shot setting, but so far explorations of MTF have focused …

Large language models (LLMs) that have been trained on multilingual but not parallel text
exhibit a remarkable ability to translate between languages. We probe this ability in an in …

Multilingual Large Language Models are capable of using powerful Large Language
Models to handle and respond to queries in multiple languages, which achieves remarkable …

While the recent Chain-of-Thought (CoT) technique enhances the reasoning ability of large
language models (LLMs) with the theory of mind, it might still struggle in handling logical …

Existing language models (LMs) predict tokens with a softmax over a finite vocabulary,
which can make it difficult to predict rare tokens or phrases. We introduce NPM, the first …

Most language models (LMs) are trained and applied in an autoregressive left-to-right
fashion, predicting the next token from the preceding ones. However, this ignores that the full …

Large language models (LLMs), such as OpenAI's Codex, have demonstrated their potential
to generate code from natural language descriptions across a wide range of programming …

Abstract Do the Spratly Islands belong to China, the Philippines, or Vietnam? A pretrained
large language model (LLM) may answer differently if asked in the languages of each …