Recent advances in natural language processing (NLP) have led to the
dev...
Recent advances in NLP have significantly improved the performance of
la...
Zero-shot cross-lingual transfer learning has been shown to be highly
ch...
Linking neural representations to linguistic factors is crucial in order...
We propose a generative model for text generation, which exhibits
disent...
The problem of comparing two bodies of text and searching for words that...
Recent impressive improvements in NLP, largely based on the success of
c...
This work explores the capacities of character-based Neural Machine
Tran...
This work takes a critical look at the evaluation of user-generated cont...
Access to large pre-trained models of varied architectures, in many diff...
Semi-Supervised Variational Autoencoders (SSVAEs) are widely used models...
Multilingual pretrained language models have demonstrated remarkable
zer...
NLP Interpretability aims to increase trust in model predictions. This m...
Today, interpretability of Black-Box Natural Language Processing (NLP) m...
We present an unsupervised method to obtain disentangled representations...
This article presents a discussion on the main linguistic phenomena whic...
Transfer learning based on pretraining language models on a large amount...
Coupled with the availability of large scale datasets, deep learning
arc...
Even though Variational Autoencoders (VAEs) are widely used for
semi-sup...
Building natural language processing systems for non standardized and lo...
Pretrained language models are now ubiquitous in Natural Language Proces...