Semi-structured explanation depicts the implicit process of a reasoner w...
Adversarial robustness, domain generalization and dataset biases are thr...
Large language models (LLMs) have shown great abilities of solving vario...
Dialogue acts (DAs) can represent conversational actions of tutors or
st...
Dialogue Acts (DAs) can be used to explain what expert tutors do and wha...
Current work in named entity recognition (NER) uses either cross entropy...
Domain adaptation is an effective solution to data scarcity in low-resou...
Text simplification is the task of rewriting a text so that it is readab...
We study acquisition functions for active learning (AL) for text
classif...
Multilingual Neural Machine Translation (MNMT) trains a single NMT model...
Deep generative models have been widely used in several areas of NLP, an...
Neural topic models (NTMs) apply deep neural networks to topic modelling...
This paper proposes a transformer over transformer framework, called
Tra...
Topic modelling has been a successful technique for text analysis for al...
Software Quality Assurance (SQA) planning aims to define proactive plans...
Predicting (1) when the next hospital admission occurs and (2) what will...
Supervised learning, characterized by both discriminative and generative...
Scarcity of parallel sentence-pairs poses a significant hurdle for train...
In this paper, we present a new topic modelling approach via the theory ...
Modern deep learning methods have equipped researchers and engineers wit...
Electronic medical record (EMR) data contains historical sequences of vi...
Graph embedding methods transform high-dimensional and complex graph con...
As we rely more and more on machine learning models for real-life
decisi...
Many applications, such as text modelling, high-throughput sequencing, a...
Recently, considerable research effort has been devoted to developing de...
The questions in a crowdsourcing task typically exhibit varying degrees ...
Besides the text content, documents and their associated words usually c...
This paper introduces a novel parameter estimation method for the probab...
Relational data are usually highly incomplete in practice, which inspire...
Bibliographic analysis considers author's research areas, the citation
n...
The Dirichlet process and its extension, the Pitman-Yor process, are
sto...
Bibliographic analysis considers the author's research areas, the citati...
We develop dependent hierarchical normalized random measures and apply t...
This paper presents theory for Normalized Random Measures (NRMs), Normal...