23 citations · 157 across the 46 of their papers we have counts for
12 papers · 1 filter
Routine Outcome Monitoring in Psychotherapy Treatment using Sentiment-Topic Modelling Approach
Noor Fazilla Abd Yusof, Chenghua Lin
Despite the importance of emphasizing the right psychotherapy treatment for an individual patient, assessing the outcome of the therapy session is equally crucial. Evidence showed…
MAP-Music2Vec: A Simple and Effective Baseline for Self-Supervised Music Audio Representation Learning
Yizhi Li, Ruibin Yuan, Ge Zhang +11
The deep learning community has witnessed an exponentially growing interest in self-supervised learning (SSL). However, it still remains unexplored how to build a framework for lea…
HERB: Measuring Hierarchical Regional Bias in Pre-trained Language Models
Yizhi Li, Ge Zhang, Bohao Yang +4
Fairness has become a trending topic in natural language processing (NLP), which addresses biases targeting certain social groups such as genders and religions. However, regional b…
Improving Variational Autoencoders with Density Gap-based Regularization
Jianfei Zhang, Jun Bai, Chenghua Lin +2
Variational autoencoders (VAEs) are one of the powerful unsupervised learning frameworks in NLP for latent representation learning and latent-directed generation. The classic optim…
EtriCA: Event-Triggered Context-Aware Story Generation Augmented by Cross Attention
Chen Tang, Chenghua Lin, Henglin Huang +2
One of the key challenges of automatic story generation is how to generate a long narrative that can maintain fluency, relevance, and coherence. Despite recent progress, current st…
Improving Chinese Story Generation via Awareness of Syntactic Dependencies and Semantics
Henglin Huang, Chen Tang, Tyler Loakman +2
Story generation aims to generate a long narrative conditioned on a given input. In spite of the success of prior works with the application of pre-trained models, current neural m…
NGEP: A Graph-based Event Planning Framework for Story Generation
Chen Tang, Zhihao Zhang, Tyler Loakman +2
To improve the performance of long text generation, recent studies have leveraged automatically planned event structures (i.e. storylines) to guide story generation. Such prior wor…
Terminology-aware Medical Dialogue Generation
Chen Tang, Hongbo Zhang, Tyler Loakman +2
Medical dialogue generation aims to generate responses according to a history of dialogue turns between doctors and patients. Unlike open-domain dialogue generation, this requires…
Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature
Tomas Goldsack, Zhihao Zhang, Chenghua Lin +1
Lay summarisation aims to jointly summarise and simplify a given text, thus making its content more comprehensible to non-experts. Automatic approaches for lay summarisation can pr…
Nominal Metaphor Generation with Multitask Learning
Yucheng Li, Chenghua Lin, Frank Geurin
Metaphor generation is a challenging task which can impact many downstream tasks such as improving user satisfaction with dialogue systems and story generation. This paper tackles…
TranSHER: Translating Knowledge Graph Embedding with Hyper-Ellipsoidal Restriction
Yizhi Li, Wei Fan, Chao Liu +2
Knowledge graph embedding methods are important for the knowledge graph completion (or link prediction) task. One existing efficient method, PairRE, leverages two separate vectors…
Recent Advances in Neural Text Generation: A Task-Agnostic Survey
Chen Tang, Frank Guerin, Chenghua Lin
In recent years, considerable research has been dedicated to the application of neural models in the field of natural language generation (NLG). The primary objective is to generat…