Scientific knowledge is predominantly stored in books and scientific
jou...
We release Code Llama, a family of large language models for code based ...
In this work, we develop and release Llama 2, a collection of pretrained...
This survey reviews works in which language models (LMs) are augmented w...
Language models (LMs) exhibit remarkable abilities to solve new tasks fr...
Text Summarization is a popular task and an active area of research for ...
Instruction tuning enables pretrained language models to perform new tas...
Information overload is a major obstacle to scientific progress. The
exp...
Existing metrics for evaluating the quality of automatically generated
q...
Recent work on large language models relies on the intuition that most
n...
Language models generate texts by successively predicting probability
di...
Grounded text generation systems often generate text that contains factu...
Generative Adversarial Networks (GANs) have known a tremendous success f...
Natural language processing (NLP) systems are increasingly trained to
ge...
Transformer-based pre-training techniques of text and layout have proven...
In this paper, we propose QACE, a new metric based on Question Answering...
Due to the discrete nature of words, language GANs require to be optimiz...
Automatic evaluation remains an open research question in Natural Langua...
In this paper, we explore how QuestEval, which is a Text-vs-Text metric,...
Summarization evaluation remains an open research problem: current metri...
Coupled with the availability of large scale datasets, deep learning
arc...
In the context of chit-chat dialogues it has been shown that endowing sy...
Motivated by the lack of data for non-English languages, in particular f...
Training regimes based on Maximum Likelihood Estimation (MLE) suffer fro...
We present MLSUM, the first large-scale MultiLingual SUMmarization datas...
Pre-trained language models such as BERT have recently contributed to
si...
We introduce a novel approach for sequence decoding, Discriminative
Adve...
We propose a novel text generation task, namely Curiosity-driven Questio...
Abstractive summarization approaches based on Reinforcement Learning (RL...