Neural language models are increasingly deployed into APIs and websites ...
The generations of large language models are commonly controlled through...
Large language models are now tuned to align with the goals of their
cre...
Pretraining is the preliminary and fundamental step in developing capabl...
Image diffusion models such as DALL-E 2, Imagen, and Stable Diffusion ha...
As text generated by large language models proliferates, it becomes vita...
Recent developments in natural language generation (NLG) using neural
la...
Studying data memorization in neural language models helps us understand...
AI researchers have posited Dungeons and Dragons (D D) as a challenge ...
The task of inserting text into a specified position in a passage, known...
Large language models have been shown to achieve remarkable performance
...
While popular televised events such as presidential debates or TV shows ...
Large language models (LMs) have been shown to memorize parts of their
t...
Modern neural language models widely used in tasks across NLP risk memor...
NLP researchers need more, higher-quality text datasets. Human-labeled
d...
In this paper, we leverage large language models (LMs) to perform zero-s...
As neural language models grow in effectiveness, they are increasingly b...
We find that existing language modeling datasets contain many near-dupli...
In recent years, large neural networks for natural language generation (...
We propose a sentence-level language model which selects the next senten...
For open-ended language generation tasks such as storytelling and dialog...
Contact tracing is an essential tool for public health officials and loc...
With the advent of generative models with a billion parameters or more, ...
While conditional language models have greatly improved in their ability...
We propose a new method for learning a representation of image motion in...