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09/15/2023
Reward Engineering for Generating Semi-structured Explanation
Semi-structured explanation depicts the implicit process of a reasoner w...
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06/27/2023
A Survey on Out-of-Distribution Evaluation of Neural NLP Models
Adversarial robustness, domain generalization and dataset biases are thr...
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05/21/2023
PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMs
Large language models (LLMs) have shown great abilities of solving vario...
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04/15/2023
Robust Educational Dialogue Act Classifiers with Low-Resource and Imbalanced Datasets
Dialogue acts (DAs) can represent conversational actions of tutors or st...
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04/12/2023
Does Informativeness Matter? Active Learning for Educational Dialogue Act Classification
Dialogue Acts (DAs) can be used to explain what expert tutors do and wha...
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12/09/2022
AUC Maximization for Low-Resource Named Entity Recognition
Current work in named entity recognition (NER) uses either cross entropy...
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11/11/2022
Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios
Domain adaptation is an effective solution to data scarcity in low-resou...
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06/10/2022
Unsupervised Sentence Simplification via Dependency Parsing
Text simplification is the task of rewriting a text so that it is readab...
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10/27/2021
Diversity Enhanced Active Learning with Strictly Proper Scoring Rules
We study acquisition functions for active learning (AL) for text classif...
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10/15/2021
Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?
Multilingual Neural Machine Translation (MNMT) trains a single NMT model...
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10/14/2021
The Neglected Sibling: Isotropic Gaussian Posterior for VAE
Deep generative models have been widely used in several areas of NLP, an...
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10/14/2021
Neural Attention-Aware Hierarchical Topic Model
Neural topic models (NTMs) apply deep neural networks to topic modelling...
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10/14/2021
Transformer over Pre-trained Transformer for Neural Text Segmentation with Enhanced Topic Coherence
This paper proposes a transformer over transformer framework, called Tra...
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02/28/2021
Topic Modelling Meets Deep Neural Networks: A Survey
Topic modelling has been a successful technique for text analysis for al...
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02/19/2021
SQAPlanner: Generating Data-Informed Software Quality Improvement Plans
Software Quality Assurance (SQA) planning aims to define proactive plans...
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02/04/2021
Temporal Cascade and Structural Modelling of EHRs for Granular Readmission Prediction
Predicting (1) when the next hospital admission occurs and (2) what will...
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11/12/2020
Discriminative, Generative and Self-Supervised Approaches for Target-Agnostic Learning
Supervised learning, characterized by both discriminative and generative...
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10/12/2020
Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation
Scarcity of parallel sentence-pairs poses a significant hurdle for train...
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08/12/2020
Neural Sinkhorn Topic Model
In this paper, we present a new topic modelling approach via the theory ...
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07/14/2020
Hands-on Bayesian Neural Networks – a Tutorial for Deep Learning Users
Modern deep learning methods have equipped researchers and engineers wit...
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12/08/2019
MedGraph: Structural and Temporal Representation Learning of Electronic Medical Records
Electronic medical record (EMR) data contains historical sequences of vi...
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12/02/2019
Gaussian Embedding of Large-scale Attributed Graphs
Graph embedding methods transform high-dimensional and complex graph con...
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08/11/2019
LoRMIkA: Local Rule-based Model Interpretability with k-optimal Associations
As we rely more and more on machine learning models for real-life decisi...
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05/02/2019
Deep Generative Models for Sparse, High-dimensional, and Overdispersed Discrete Data
Many applications, such as text modelling, high-throughput sequencing, a...
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11/02/2018
Dirichlet belief networks for topic structure learning
Recently, considerable research effort has been devoted to developing de...
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02/12/2018
Distinguishing Question Subjectivity from Difficulty for Improved Crowdsourcing
The questions in a crowdsourcing task typically exhibit varying degrees ...
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09/19/2017
MetaLDA: a Topic Model that Efficiently Incorporates Meta information
Besides the text content, documents and their associated words usually c...
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08/25/2017
Accurate parameter estimation for Bayesian Network Classifiers using Hierarchical Dirichlet Processes
This paper introduces a novel parameter estimation method for the probab...
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06/14/2017
Leveraging Node Attributes for Incomplete Relational Data
Relational data are usually highly incomplete in practice, which inspire...
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09/22/2016
Bibliographic Analysis with the Citation Network Topic Model
Bibliographic analysis considers author's research areas, the citation n...
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09/22/2016
Nonparametric Bayesian Topic Modelling with the Hierarchical Pitman-Yor Processes
The Dirichlet process and its extension, the Pitman-Yor process, are sto...
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09/21/2016
Bibliographic Analysis on Research Publications using Authors, Categorical Labels and the Citation Network
Bibliographic analysis considers the author's research areas, the citati...
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06/18/2012
Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling
We develop dependent hierarchical normalized random measures and apply t...
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05/18/2012
