We propose an unsupervised approach to paraphrasing multiword expression...
A series of datasets and models have been proposed for summaries generat...
Various evaluation metrics exist for natural language generation tasks, ...
State-sponsored trolls are the main actors of influence campaigns on soc...
Multi-document summarization (MDS) aims to generate a summary for a numb...
While pre-trained language models can generate individually fluent sente...
Negation is poorly captured by current language models, although the ext...
Visual-Semantic Embedding (VSE) aims to learn an embedding space where
r...
In this paper we report on our submission to the Multidocument Summarisa...
We propose a new unsupervised method for lexical substitution using
pre-...
Natural language processing (NLP) has a significant impact on society vi...
Data artifacts incentivize machine learning models to learn non-transfer...
NLP research is impeded by a lack of resources and awareness of the
chal...
We present PeerSum, a new MDS dataset using peer reviews of scientific
p...
This paper describes the submissions of the Natural Language Processing ...
Conversation disentanglement, the task to identify separate threads in
c...
GPT-2 has been frequently adapted in story generation models as it provi...
Most rumour detection models for social media are designed for one speci...
We present IndoBERTweet, the first large-scale pretrained model for
Indo...
There is unison is the scientific community about human induced climate
...
While automatic summarization evaluation methods developed for English a...
The COVID-19 pandemic has driven ever-greater demand for tools which ena...
Existing work on probing of pretrained language models (LMs) has
predomi...
We introduce a grey-box adversarial attack and defence framework for
sen...
We introduce a top-down approach to discourse parsing that is conceptual...
In this paper, we propose FFCI, a framework for automatic summarization
...
In this paper, we introduce a large-scale Indonesian summarization datas...
Although the Indonesian language is spoken by almost 200 million people ...
We propose a new approach for learning contextualised cross-lingual word...
We present COVID-SEE, a system for medical literature discovery based on...
Promptly and accurately answering questions on products is important for...
As part of growing NLP capabilities, coupled with an awareness of the et...
The world is facing the challenge of climate crisis. Despite the consens...
We study the influence of context on sentence acceptability. First we co...
An adversarial example is an input transformed by small perturbations th...
Despite the success of attention-based neural models for natural languag...
In this paper, we propose a joint architecture that captures language, r...
The versatility of word embeddings for various applications is attractin...
We propose an end-to-end neural network to predict the geolocation of a
...
Topic models jointly learn topics and document-level topic distribution....
Language models are typically applied at the sentence level, without acc...
Topics generated by topic models are typically represented as list of te...
Recently, Le and Mikolov (2014) proposed doc2vec as an extension to word...