Yongbin Liu

Ensemble Making Few-Shot Learning Stronger

2021 · arXiv (Cornell University)

Few-shot learning has been proposed and rapidly emerging as a viable means for completing various tasks. Many few-shot models have been widely used for relation learning tasks. However, each of these models has a shortage …

Joint span and token framework for few-shot named entity recognition

2023 · AI Open

Few-shot Named Entity Recognition (NER) is a challenging task that involves identifying new entity types using a limited number of labeled instances for training. Currently, the majority of Few-shot NER methods are based on span, …

Few-Shot Document-Level Relation Extraction with Representation Enhance and Counterfactual Analiysis

2023

Few-shot document-level relation extraction poses a more complex and challenging task compared to sentence-level relation extraction. It also features a more realistic schema, especially in its NOTA (none-of-the-above) distribution. This paper proposes two improvements to …