The ability of humans to create and disseminate culture is often credited as the single most
important factor of our success as a species. In this Perspective, we explore the notion of …

Text Generation aims to produce plausible and readable text in human language from input
data. The resurgence of deep learning has greatly advanced this field, in particular, with the …

Large language models have been demonstrated to be valuable in different fields. ChatGPT,
developed by OpenAI, has been trained using massive amounts of data and simulates …

We introduce a new type of test, called a Turing Experiment (TE), for evaluating to what
extent a given language model, such as GPT models, can simulate different aspects of …

Through considerable effort and intuition, several recent works have reverse-engineered
nontrivial behaviors oftransformer models. This paper systematizes the mechanistic …

Recent work has shown exciting promise in updating large language models with new
memories, so as to replace obsolete information or add specialized knowledge. However …

We analyze the storage and recall of factual associations in autoregressive transformer
language models, finding evidence that these associations correspond to localized, directly …

Making language models bigger does not inherently make them better at following a user's
intent. For example, large language models can generate outputs that are untruthful, toxic, or …

Large language models (LLMs) are being integrated into healthcare systems; but these
models may recapitulate harmful, race-based medicine. The objective of this study is to …

Research in mechanistic interpretability seeks to explain behaviors of machine learning
models in terms of their internal components. However, most previous work either focuses …