11 citations · 22 across the 6 of their papers we have counts for
6 papers
DPL: Decoupled Prototype Learning for Enhancing Robustness of Vision-Language Transformers to Missing Modalities
Jueqing Lu, Yuanyuan Qi, Xiaohao Yang +8
The performance of Visio-Language Transformers drops sharply when an input modality (e.g., image) is missing, because the model is forced to make predictions using incomplete infor…
How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses
Jionghao Lin, Eason Chen, Zeifei Han +5
Automated explanatory feedback systems play a crucial role in facilitating learning for a large cohort of learners by offering feedback that incorporates explanations, significantl…
Harnessing the Power of Beta Scoring in Deep Active Learning for Multi-Label Text Classification
Wei Tan, Ngoc Dang Nguyen, Lan Du +1
Within the scope of natural language processing, the domain of multi-label text classification is uniquely challenging due to its expansive and uneven label distribution. The compl…
Bayesian Estimate of Mean Proper Scores for Diversity-Enhanced Active Learning
Wei Tan, Lan Du, Wray Buntine
The effectiveness of active learning largely depends on the sampling efficiency of the acquisition function. Expected Loss Reduction (ELR) focuses on a Bayesian estimate of the red…
Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help?
Ngoc Dang Nguyen, Wei Tan, Lan Du +3
Named entity recognition (NER), a task that identifies and categorizes named entities such as persons or organizations from text, is traditionally framed as a multi-class classific…
Re-weighting Tokens: A Simple and Effective Active Learning Strategy for Named Entity Recognition
Haocheng Luo, Wei Tan, Ngoc Dang Nguyen +1
Active learning, a widely adopted technique for enhancing machine learning models in text and image classification tasks with limited annotation resources, has received relatively…