1 code implementation • NAACL 2022 • Xiaochen Wang, Yue Wang
As a fundamental task in natural language processing, named entity recognition (NER) aims to locate and classify named entities in unstructured text.
1 code implementation • 19 Apr 2024 • Xiaokun Zhang, Bo Xu, Zhaochun Ren, Xiaochen Wang, Hongfei Lin, Fenglong Ma
At the item level, we introduce a co-occurrence representation schema to explicitly incorporate cooccurrence patterns into ID representations.
no code implementations • 25 Feb 2024 • Xiangdi Meng, Damai Dai, Weiyao Luo, Zhe Yang, Shaoxiang Wu, Xiaochen Wang, Peiyi Wang, Qingxiu Dong, Liang Chen, Zhifang Sui
Although LoRA fine-tuning is effective, there is still a performance gap compared to full fine-tuning, since its weight update is limited to low-rank matrices.
no code implementations • 24 Feb 2024 • Junyu Luo, Xiaochen Wang, Jiaqi Wang, Aofei Chang, Yaqing Wang, Fenglong Ma
Automatic International Classification of Diseases (ICD) coding plays a crucial role in the extraction of relevant information from clinical notes for proper recording and billing.
no code implementations • 2 Feb 2024 • Jiaqi Wang, Junyu Luo, Muchao Ye, Xiaochen Wang, Yuan Zhong, Aofei Chang, Guanjie Huang, Ziyi Yin, Cao Xiao, Jimeng Sun, Fenglong Ma
This survey systematically reviews recent advances in deep learning-based predictive models using EHR data.
no code implementations • 11 Nov 2023 • Xiaochen Wang, Xiao Xiao, Ruhan Zhang, Xuan Zhang, Taesik Na, Tejaswi Tenneti, Haixun Wang, Fenglong Ma
Efficient and accurate product relevance assessment is critical for user experiences and business success.
1 code implementation • 11 Oct 2023 • Xiaochen Wang, Junyu Luo, Jiaqi Wang, Ziyi Yin, Suhan Cui, Yuan Zhong, Yaqing Wang, Fenglong Ma
Pretraining has proven to be a powerful technique in natural language processing (NLP), exhibiting remarkable success in various NLP downstream tasks.
no code implementations • 4 Oct 2023 • Yuan Zhong, Suhan Cui, Jiaqi Wang, Xiaochen Wang, Ziyi Yin, Yaqing Wang, Houping Xiao, Mengdi Huai, Ting Wang, Fenglong Ma
Health risk prediction is one of the fundamental tasks under predictive modeling in the medical domain, which aims to forecast the potential health risks that patients may face in the future using their historical Electronic Health Records (EHR).
no code implementations • 2 Apr 2023 • Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang
AEHCL designs the intra-event and inter-event contrastive modules to exploit self-supervised AHIN information.
no code implementations • 19 Dec 2022 • Chengwen Wang, Qingxiu Dong, Xiaochen Wang, Haitao Wang, Zhifang Sui
Taking the Named Entity Recognition (NER) datasets as a case study, we introduce $9$ statistical metrics for a statistical dataset evaluation framework.
1 code implementation • 23 Mar 2021 • Arash Pakbin, Xiaochen Wang, Bobak J. Mortazavi, Donald K. K. Lee
Modern applications of survival analysis increasingly involve time-dependent covariates.
1 code implementation • ICML 2020 • Xiaochen Wang, Arash Pakbin, Bobak J. Mortazavi, Hongyu Zhao, Donald K. K. Lee
BoXHED 1. 0 is a novel tree-based implementation of the generic estimator proposed in Lee, Chen, Ishwaran (2017), which was designed for handling time-dependent covariates in a fully nonparametric manner.
no code implementations • 16 May 2019 • Yu Zheng, Hanqing Nan, Qihui Fan, Xiaochen Wang, LiYu Liu, Ruchuan Liu, Fangfu Ye, Bo Sun, Yang Jiao
During migration, individual cells can generate active pulling forces via actin filament contraction, which are transmitted to the ECM fibers through focal adhesion complexes, remodel the ECM, and eventually propagate to and can be sensed by other cells in the system.
no code implementations • IJCNLP 2017 • Liangming Pan, Xiaochen Wang, Chengjiang Li, Juanzi Li, Jie Tang
Massive Open Online Courses (MOOCs), offering a new way to study online, are revolutionizing education.
no code implementations • 13 Oct 2017 • Fang Zhang, Xiaochen Wang, Jingfei Han, Jie Tang, Shiyin Wang, Marie-Francine Moens
We leverage a large-scale knowledge base (Wikipedia) to generate topic embeddings using neural networks and use this kind of representations to help capture the representativeness of topics for given areas.