To better handle long-tail cases in the sequence labeling (SL) task, in ...
Inspired by recent advances in retrieval augmented methods in
NLP <cit.>...
kNN based neural machine translation (kNN-MT) has achieved
state-of-the-...
Backdoor attacks pose a new threat to NLP models. A standard strategy to...
Inspired by the notion that “to copy is easier than to memorize“, in
thi...
Pre-trained Natural Language Processing (NLP) models can be easily adapt...
In order to better simulate the real human conversation process, models ...
Semantic Role Labeling (SRL) aims at recognizing the predicate-argument
...
In this paper, we propose a new paradigm for paraphrase generation by
tr...
A long-standing issue with paraphrase generation is how to obtain reliab...
Out-of-Distribution (OOD) detection is an important problem in natural
l...
The proposed pruning strategy offers merits over weight-based pruning
te...
Recent pretraining models in Chinese neglect two important aspects speci...
The frustratingly fragile nature of neural network models make current
n...
Though nearest neighbor Machine Translation (kNN-MT)
<cit.> has proved t...
The standard way to estimate the parameters Θ_SEIR (e.g., the
transmissi...
Higher-order methods for dependency parsing can partially but not fully
...
Existing methods to measure sentence similarity are faced with two
chall...
In this work, we propose BertGCN, a model that combines large scale
pret...
Existing approaches to explaining deep learning models in NLP usually su...
The goal of semi-supervised learning is to utilize the unlabeled, in-dom...
Long-text generation remains a challenge. The difficulty of generating
c...
Supervised neural networks, which first map an input x to a single
repre...
While the self-attention mechanism has been widely used in a wide variet...
Maximum Mutual information (MMI), which models the bidirectional depende...
Non-autoregressive translation (NAT) models generate multiple tokens in ...
Many NLP tasks such as tagging and machine reading comprehension are fac...
The task of named entity recognition (NER) is normally divided into nest...
In this paper, we investigate the problem of training neural machine
tra...
In this paper, we propose a new strategy for the task of named entity
re...
In this paper, we aim at tackling a general issue in NLP tasks where som...
Segmenting a chunk of text into words is usually the first step of proce...
It is intuitive that NLP tasks for logographic languages like Chinese sh...