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 …

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 …

Evaluating large language model (LLM) based chat assistants is challenging due to their
broad capabilities and the inadequacy of existing benchmarks in measuring human …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

Because" out-of-the-box" large language models are capable of generating a great deal of
objectionable content, recent work has focused on aligning these models in an attempt to …

Large language models (LLMs) have revolutionized the field of artificial intelligence,
enabling natural language processing tasks that were previously thought to be exclusive to …

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 …

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 …

This paper presents an experimental study regarding the use of OpenAI's ChatGPT for
robotics applications. We outline a strategy that combines design principles for prompt …

With the rapid progress of large language models (LLMs), many downstream NLP tasks can
be well solved given appropriate prompts. Though model developers and researchers work …