While large language models (LLMs) have demonstrated remarkable capabili...
Modeling discourse – the linguistic phenomena that go beyond individual
...
One challenge in text-to-image (T2I) generation is the inadvertent refle...
Although instruction-tuned large language models (LLMs) have exhibited
r...
Pretrained language models (PLMs) have produced substantial improvements...
In real-world systems, scaling has been critical for improving the
trans...
Recent advances in large language models have enabled them to reach a le...
Zero pronouns (ZPs) are frequently omitted in pro-drop languages (e.g.
C...
Machine Translation (MT) has made significant progress in recent years u...
Relation Extraction (RE) is a crucial task in Information Extraction, wh...
Large language models (LLMs) such as Chat-GPT can produce coherent, cohe...
Knowledge-aided dialogue response generation aims at augmenting chatbots...
Recently, a new training oaxe loss has proven effective to ameliorate th...
Pre-training (PT) and back-translation (BT) are two simple and powerful
...
Previous studies have shown that initializing neural machine translation...
Non-autoregressive translation (NAT) significantly accelerates the infer...
Knowledge distillation (KD) is commonly used to construct synthetic data...
Automatic machine translation is super efficient to produce translations...
Encoder layer fusion (EncoderFusion) is a technique to fuse all the enco...
Knowledge distillation (KD) is essential for training non-autoregressive...
Non-autoregressive translation (NAT) significantly accelerates the infer...
There have been significant efforts to interpret the encoder of
Transfor...
Modern neural machine translation (NMT) models employ a large number of
...
Self-attention networks (SANs) with selective mechanism has produced
sub...
Position encoding (PE), an essential part of self-attention networks (SA...
The key challenge of multi-domain translation lies in simultaneously enc...
Although self-attention networks (SANs) have advanced the state-of-the-a...
Zero pronouns (ZPs) are frequently omitted in pro-drop languages, but sh...
Although neural machine translation (NMT) has advanced the state-of-the-...
In this work, we present novel approaches to exploit sentential context ...
Self-attention networks (SAN) have attracted a lot of interests due to t...
Self-attention networks (SANs) have drawn increasing interest due to the...
Recently, the Transformer model that is based solely on attention mechan...
With the promising progress of deep neural networks, layer aggregation h...
Neural machine translation (NMT) models generally adopt an encoder-decod...
Self-attention network (SAN) has recently attracted increasing interest ...
Pronouns are frequently omitted in pro-drop languages, such as Chinese,
...
Although there are increasing and significant ties between China and
Por...
Statistical machine translation (SMT) systems perform poorly when it is
...
Pronouns are frequently omitted in pro-drop languages, such as Chinese,
...
In translation, considering the document as a whole can help to resolve
...
In this paper, a novel approach is proposed to automatically construct
p...
Dropped Pronouns (DP) in which pronouns are frequently dropped in the so...