Recent works have empirically analyzed in-context learning and shown tha...
Despite a growing interest in diffusion-based language models, existing ...
Large language models (LLMs) have shown promise for automatic summarizat...
Sampling diverse programs from a code language model and reranking with ...
Datasets scraped from the internet have been critical to the successes o...
Controlling the behavior of language models (LMs) without re-training is...
While pretrained language models (PLMs) have greatly improved text
gener...
Overparameterized neural networks can be highly accurate on average on a...
We study textual autocomplete—the task of predicting a full sentence fro...
Language models are generally trained on data spanning a wide range of t...
How can we measure whether a natural language generation system produces...
For the task of generating complex outputs such as source code, editing
...
Machine learning models (e.g., speech recognizers) are usually trained t...
We develop an algorithm for minimizing a function using n batched functi...
Our goal is to extract meaningful transformations from raw images, such ...
We propose a new generative model of sentences that first samples a prot...
Large unweighted directed graphs are commonly used to capture relations
...
Continuous vector representations of words and objects appear to carry
s...
We analyze directed, unweighted graphs obtained from x_i∈R^d by
connecti...