44 citations · 142 across the 15 of their papers we have counts for
5 papers · 1 filter
Prompt-Learning for Fine-Grained Entity Typing
Ning Ding, Yulin Chen, Xu Han +6
As an effective approach to tune pre-trained language models (PLMs) for specific tasks, prompt-learning has recently attracted much attention from researchers. By using \textit{clo…
Crowdsourcing Learning as Domain Adaptation: A Case Study on Named Entity Recognition
Xin Zhang, Guangwei Xu, Yueheng Sun +2
Crowdsourcing is regarded as one prospective solution for effective supervised learning, aiming to build large-scale annotated training data by crowd workers. Previous studies focu…
Few-NERD: A Few-Shot Named Entity Recognition Dataset
Ning Ding, Guangwei Xu, Yulin Chen +5
Recently, considerable literature has grown up around the theme of few-shot named entity recognition (NER), but little published benchmark data specifically focused on the practica…
Probing BERT in Hyperbolic Spaces
Boli Chen, Yao Fu, Guangwei Xu +4
Recently, a variety of probing tasks are proposed to discover linguistic properties learned in contextualized word embeddings. Many of these works implicitly assume these embedding…
Prototypical Representation Learning for Relation Extraction
Ning Ding, Xiaobin Wang, Yao Fu +7
Recognizing relations between entities is a pivotal task of relational learning. Learning relation representations from distantly-labeled datasets is difficult because of the abund…