Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation-Maximization Framework

12 September 2019

Papers citing "Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation-Maximization Framework"

5 / 5 papers shown

Title
SENT: Sentence-level Distant Relation Extraction via Negative Training Ruotian Ma Tao Gui Linyang Li Qi Zhang Yaqian Zhou Xuanjing Huang 22 28 0 22 Jun 2021
Analysing the Noise Model Error for Realistic Noisy Label Data Michael A. Hedderich D. Zhu Dietrich Klakow NoLa 31 19 0 24 Jan 2021
Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction Tong Zhu Haitao Wang Junjie Yu Xiabing Zhou Wenliang Chen Wei Zhang Min Zhang 16 18 0 30 Oct 2020
A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios Michael A. Hedderich Lukas Lange Heike Adel Jannik Strötgen Dietrich Klakow 224 287 0 23 Oct 2020
Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on African Languages Michael A. Hedderich David Ifeoluwa Adelani D. Zhu Jesujoba Oluwadara Alabi Udia Markus Dietrich Klakow 17 72 0 07 Oct 2020