Rethinking Generalization of Neural Models: A Named Entity Recognition
Case Study

Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study

12 January 2020

Xuanjing Huang

Papers citing "Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study"

9 / 9 papers shown

Title
From Large to Super-Tiny: End-to-End Optimization for Cost-Efficient LLMs Jiliang Ni Jiachen Pu Zhongyi Yang Kun Zhou Hui Wang Xiaoliang Xiao Dakui Wang Xin Li Jingfeng Luo Conggang Hu 32 0 0 18 Apr 2025
FeDeRA:Efficient Fine-tuning of Language Models in Federated Learning Leveraging Weight Decomposition Yuxuan Yan Qianqian Yang Shunpu Tang Zhiguo Shi 38 13 0 29 Apr 2024
Searching for Optimal Subword Tokenization in Cross-domain NER Ruotian Ma Yiding Tan Xin Zhou Xuanting Chen Di Liang Sirui Wang Wei Yu Wu Tao Gui Qi Zhang OOD 41 14 0 07 Jun 2022
Automatic Correction of Syntactic Dependency Annotation Differences Andrew Zupon A. Carnie Michael Hammond Mihai Surdeanu 20 1 0 15 Jan 2022
Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction Bruno Taillé Vincent Guigue Geoffrey Scoutheeten Patrick Gallinari 71 5 0 24 Sep 2021
How Do Your Biomedical Named Entity Recognition Models Generalize to Novel Entities? Hyunjae Kim Jaewoo Kang AI4CE 78 21 0 01 Jan 2021
CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems Yiran Chen Pengfei Liu Ming Zhong Zi-Yi Dou Danqing Wang Xipeng Qiu Xuanjing Huang ELM 25 24 0 11 Oct 2020
On Robustness and Bias Analysis of BERT-based Relation Extraction Luoqiu Li Xiang Chen Hongbin Ye Zhen Bi Shumin Deng Ningyu Zhang Huajun Chen 24 18 0 14 Sep 2020
Design Challenges and Misconceptions in Neural Sequence Labeling Jie Yang Shuailong Liang Yue Zhang 118 161 0 12 Jun 2018