Learning with Noise: Enhance Distantly Supervised Relation Extraction
with Dynamic Transition Matrix

Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrix

11 May 2017

Zheng Wang

Rui Yan

Dongyan Zhao

Papers citing "Learning with Noise: Enhance Distantly Supervised Relation Extraction with Dynamic Transition Matrix"

9 / 9 papers shown

Title
WRENCH: A Comprehensive Benchmark for Weak Supervision Jieyu Zhang Yue Yu Yinghao Li Yujing Wang Yaming Yang Mao Yang Alexander Ratner 14 110 0 23 Sep 2021
O2D2: Out-Of-Distribution Detector to Capture Undecidable Trials in Authorship Verification Benedikt T. Boenninghoff R. M. Nickel D. Kolossa OODD 32 12 0 30 Jun 2021
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 21 19 0 24 Jan 2021
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 71 0 07 Oct 2020
Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction Christoph Alt Marc Hübner Leonhard Hennig 13 119 0 19 Jun 2019
Learning to Denoise Distantly-Labeled Data for Entity Typing Yasumasa Onoe Greg Durrett 18 57 0 04 May 2019
Combining Distant and Direct Supervision for Neural Relation Extraction Iz Beltagy Kyle Lo Bridger Waleed Ammar NoLa 11 26 0 30 Oct 2018
FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation Xu Han Hao Zhu Pengfei Yu Ziyun Wang Y. Yao Zhiyuan Liu Maosong Sun SLR 17 601 0 24 Oct 2018