As increasingly sophisticated language models emerge, their trustworthin...
We present a scalable method to build a high quality instruction followi...
The remarkable advancements in large language models (LLMs) have
signifi...
Instruction tuning enables language models to generalize more effectivel...
This survey reviews works in which language models (LMs) are augmented w...
Language models (LMs) exhibit remarkable abilities to solve new tasks fr...
Instruction tuning enables pretrained language models to perform new tas...
We study the problem of retrieval with instructions, where users of a
re...
Few-shot classification in NLP has recently made great strides due to th...
Evaluation of text generation to date has primarily focused on content
c...
Textual content is often the output of a collaborative writing process: ...
Large language models have shown impressive few-shot results on a wide r...
Verifiability is a core content policy of Wikipedia: claims that are lik...
Pretrained language models (PLMs) have achieved superhuman performance o...
Due to the high costs associated with finetuning large language models,
...
Prompt-based approaches are strong at few-shot learning. However, Perez ...
To obtain high-quality sentence embeddings from pretrained language mode...
When trained on large, unfiltered crawls from the internet, language mod...
Providing pretrained language models with simple task descriptions or pr...
A recent approach for few-shot text classification is to convert textual...
When scaled to hundreds of billions of parameters, pretrained language m...
Some NLP tasks can be solved in a fully unsupervised fashion by providin...
Pretraining deep contextualized representations using an unsupervised
la...
Pretraining deep neural network architectures with a language modeling
o...
Learning high-quality embeddings for rare words is a hard problem becaus...
Word embeddings are a key component of high-performing natural language
...
This work addresses the task of generating English sentences from Abstra...