no code implementations • SemEval (NAACL) 2022 • Zihang Liu, Yancheng He, Feiqing Zhuang, Bing Xu
Respectively, for subtask 1, that is, to judge whether a sentence is PCL, the method of retraining the model with specific task data is adopted, and the method of splicing [CLS] and the keyword representation of the last three layers as the representation of the sentence; for subtask 2, that is, to judge the PCL type of the sentence, in addition to using the same method as task1, the method of selecting a special loss for Multi-label text classification is applied.
Multi Label Text Classification Multi-Label Text Classification +2
1 code implementation • 22 Aug 2023 • Zihang Liu, Le Yu, Tongyu Zhu, Leiei Sun
Spatial-temporal data modeling aims to mine the underlying spatial relationships and temporal dependencies of objects in a system.
1 code implementation • 11 Oct 2022 • Yunhao Du, Zihang Liu, Fei Su
Multiple Object Tracking (MOT) has rapidly progressed in recent years.
1 code implementation • 12 Apr 2022 • Le Yu, Zihang Liu, Leilei Sun, Bowen Du, Chuanren Liu, Weifeng Lv
Previous studies for temporal sets prediction mainly focus on the modelling of elements and implicitly represent each user's preference based on his/her interacted elements.
no code implementations • 12 Feb 2022 • Zihang Liu, Chunhui Zhao
In this paper, a novel geometry-aware semi-supervised learning framework is proposed for medical image segmentation, which is a consistency-based method.