Cross-lingual summarization consists of generating a summary in one lang...
While conditional generation models can now generate natural language we...
Modern deep models for summarization attains impressive benchmark
perfor...
Abstractive summarization has enjoyed renewed interest in recent years,
...
We consider the problem of automatically generating stories in multiple
...
Large language models (LLMs) have been shown to perform well in answerin...
Conditional language models are predominantly trained with maximum likel...
Widely used evaluation metrics for text generation either do not work we...
The ability to convey relevant and faithful information is critical for ...
We propose Composition Sampling, a simple but effective method to genera...
One of the most challenging aspects of current single-document news
summ...
Professional summaries are written with document-level information, such...
Pre-trained transformer-based sequence-to-sequence models have become th...
We introduce GEM, a living benchmark for natural language Generation (NL...
We propose encoder-centric stepwise models for extractive summarization ...
It is well known that the standard likelihood training and approximate
d...
Recent trends in natural language processing using pretraining have shif...
Neural conditional text generation systems have achieved significant pro...
Unsupervised pre-training of large neural models has recently revolution...
We introduce 'extreme summarization', a new single-document summarizatio...
There has been substantial progress in summarization research enabled by...
We present a new neural model for text summarization that first extracts...
We present a new neural model for text summarization that first extracts...
This article deals with adversarial attacks towards deep learning system...
We introduce extreme summarization, a new single-document summarization ...
Single document summarization is the task of producing a shorter version...
We propose a new sentence simplification task (Split-and-Rephrase) where...
Most extractive summarization methods focus on the main body of the docu...
We describe a search algorithm for optimizing the number of latent state...
One of the limitations of semantic parsing approaches to open-domain que...
Canonical correlation analysis (CCA) is a method for reducing the dimens...
We present a novel approach to sentence simplification which departs fro...