7 citations · 15 across the 5 of their papers we have counts for
5 papers
Using Large Language Models to Provide Explanatory Feedback to Human Tutors
Jionghao Lin, Danielle R. Thomas, Feifei Han +4
Research demonstrates learners engaging in the process of producing explanations to support their reasoning, can have a positive impact on learning. However, providing learners rea…
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…
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…
Diversity Enhanced Active Learning with Strictly Proper Scoring Rules
Wei Tan, Lan Du, Wray Buntine
We study acquisition functions for active learning (AL) for text classification. The Expected Loss Reduction (ELR) method focuses on a Bayesian estimate of the reduction in classif…