no code implementations • SemEval (NAACL) 2022 • Qizhi Lin, Changyu Hou, Xiaopeng Wang, Jun Wang, Yixuan Qiao, Peng Jiang, Xiandi Jiang, Benqi Wang, Qifeng Xiao
From pretrained contextual embedding to document-level embedding, the selection and construction of embedding have drawn more and more attention in the NER domain in recent research.
no code implementations • 1 Sep 2023 • Xin Qi, Xiaopeng Wang, Zhiyong Wang, Wang Liu, Mingming Ding, Shuchen Shi
The evaluation results of our system showed a quality MOS score of 3. 6 for the Hub task and 3. 4 for the Spoke task, placing our system at an average level among all participating teams.
no code implementations • SemEval (NAACL) 2022 • Changyu Hou, Jun Wang, Yixuan Qiao, Peng Jiang, Peng Gao, Guotong Xie, Qizhi Lin, Xiaopeng Wang, Xiandi Jiang, Benqi Wang, Qifeng Xiao
By assigning different weights to each model for different inputs, we adopted the Transformer layer to integrate the advantages of diverse models effectively.
Low Resource Named Entity Recognition named-entity-recognition +2