37 citations · 89 across the 16 of their papers we have counts for
16 papers
Towards Generalising Neural Topical Representations
Xiaohao Yang, He Zhao, Dinh Phung +1
Topic models have evolved from conventional Bayesian probabilistic models to recent Neural Topic Models (NTMs). Although NTMs have shown promising performance when trained and test…
Robust Educational Dialogue Act Classifiers with Low-Resource and Imbalanced Datasets
Jionghao Lin, Wei Tan, Ngoc Dang Nguyen +6
Dialogue acts (DAs) can represent conversational actions of tutors or students that take place during tutoring dialogues. Automating the identification of DAs in tutoring dialogues…
Does Informativeness Matter? Active Learning for Educational Dialogue Act Classification
Wei Tan, Jionghao Lin, David Lang +4
Dialogue Acts (DAs) can be used to explain what expert tutors do and what students know during the tutoring process. Most empirical studies adopt the random sampling method to obta…
HiTSKT: A Hierarchical Transformer Model for Session-Aware Knowledge Tracing
Fucai Ke, Weiqing Wang, Weicong Tan +4
Knowledge tracing (KT) aims to leverage students' learning histories to estimate their mastery levels on a set of pre-defined skills, based on which the corresponding future perfor…
AUC Maximization for Low-Resource Named Entity Recognition
Ngoc Dang Nguyen, Wei Tan, Wray Buntine +3
Current work in named entity recognition (NER) uses either cross entropy (CE) or conditional random fields (CRF) as the objective/loss functions to optimize the underlying NER mode…
Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios
Ngoc Dang Nguyen, Lan Du, Wray Buntine +2
Domain adaptation is an effective solution to data scarcity in low-resource scenarios. However, when applied to token-level tasks such as bioNER, domain adaptation methods often su…