This paper investigates the direct risks and harms associated with modern text-to-image
generative models, such as DALL-E and Midjourney, through a comprehensive literature …

Human participants play a central role in the development of modern artificial intelligence
(AI) technology, in psychological science, and in user research. Recent advances in …

Large Language Models (LLMs) have made substantial progress in the past several months,
shattering state-of-the-art benchmarks in many domains. This paper investigates LLMs' …

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 …

Datasets are foundational to many breakthroughs in modern artificial intelligence. Many
recent achievements in the space of natural language processing (NLP) can be attributed to …

One widely cited barrier to the adoption of LLMs as proxies for humans in subjective tasks is
their sensitivity to prompt wording—but interestingly, humans also display sensitivities to …

There is growing consensus that language model (LM) developers should not be the sole
deciders of LM behavior, creating a need for methods that enable the broader public to …

As the reach of large language models (LMs) expands globally, their ability to cater to
diverse cultural contexts becomes crucial. Despite advancements in multilingual …

Human feedback plays a central role in the alignment of Large Language Models (LLMs).
However, open questions remain about the methods (how), domains (where), people (who) …

Large language models (LLMs) have led to a surge in collaborative writing with model
assistance. As different users incorporate suggestions from the same model, there is a risk of …