3 citations · 4 across the 5 of their papers we have counts for
5 papers
Mitigating Catastrophic Forgetting in Task-Incremental Continual Learning with Adaptive Classification Criterion
Yun Luo, Xiaotian Lin, Zhen Yang +3
Task-incremental continual learning refers to continually training a model in a sequence of tasks while overcoming the problem of catastrophic forgetting (CF). The issue arrives fo…
How to choose "Good" Samples for Text Data Augmentation
Xiaotian Lin, Nankai Lin, Yingwen Fu +2
Deep learning-based text classification models need abundant labeled data to obtain competitive performance. Unfortunately, annotating large-size corpus is time-consuming and labor…
An Efficient Framework for Few-shot Skeleton-based Temporal Action Segmentation
Leiyang Xu, Qiang Wang, Xiaotian Lin +1
Temporal action segmentation (TAS) aims to classify and locate actions in the long untrimmed action sequence. With the success of deep learning, many deep models for action segment…
Automatic dataset generation for specific object detection
Xiaotian Lin, Leiyang Xu, Qiang Wang
In the past decade, object detection tasks are defined mostly by large public datasets. However, building object detection datasets is not scalable due to inefficient image collect…
Multilingual Text Classification for Dravidian Languages
Xiaotian Lin, Nankai Lin, Kanoksak Wattanachote +2
As the fourth largest language family in the world, the Dravidian languages have become a research hotspot in natural language processing (NLP). Although the Dravidian languages co…