Spurred by the recent rapid increase in the development and distribution...
Knowledge Graph (KG)-to-Text Generation has seen recent improvements in
...
Backdoor attacks are an insidious security threat against machine learni...
The burgeoning progress in the field of Large Language Models (LLMs) her...
Modern NLP models are often trained over large untrusted datasets, raisi...
In very recent years more attention has been placed on probing the role ...
Previous works mostly focus on either multilingual or multi-domain aspec...
Previous works have validated that text generation APIs can be stolen th...
A parallel corpus is generally required to automatically evaluate the
tr...
Nowadays, due to the breakthrough in natural language generation (NLG),
...
Pre-training and then fine-tuning large language models is commonly used...
This paper considers the unsupervised domain adaptation problem for neur...
Machine-learning-as-a-service (MLaaS) has attracted millions of users to...
Semi-Supervised Learning (SSL) has seen success in many application doma...
The advances in pre-trained models (e.g., BERT, XLNET and etc) have larg...
Natural language processing (NLP) tasks, ranging from text classificatio...
Structured representations like graphs and parse trees play a crucial ro...
It has been demonstrated that hidden representation learned by a deep mo...
Most deep learning frameworks require users to pool their local data or ...
This paper introduces Dynamic Programming Encoding (DPE), a new segmenta...
In spite of the recent success of Dialogue Act (DA) classification, the
...
Sequence to sequence (SEQ2SEQ) models often lack diversity in their gene...
Dealing with the complex word forms in morphologically rich languages is...