Revisiting DocRED -- Addressing the False Negative Problem in Relation
Extraction

Revisiting DocRED -- Addressing the False Negative Problem in Relation Extraction

25 May 2022

Hwee Tou Ng

Sharifah Mahani Aljunied

Papers citing "Revisiting DocRED -- Addressing the False Negative Problem in Relation Extraction"

9 / 9 papers shown

Title
VaeDiff-DocRE: End-to-end Data Augmentation Framework for Document-level Relation Extraction Khai Phan Tran Wen Hua Xue Li SyDa 77 0 0 18 Dec 2024
DiVA-DocRE: A Discriminative and Voice-Aware Paradigm for Document-Level Relation Extraction Yiheng Wu Roman Yangarber Xian Mao 13 0 0 07 Sep 2024
Dialogue Ontology Relation Extraction via Constrained Chain-of-Thought Decoding Renato Vukovic David Arps Carel van Niekerk Benjamin Matthias Ruppik Hsien-chin Lin Michael Heck Milica Gašić 28 1 0 05 Aug 2024
MemLLM: Finetuning LLMs to Use An Explicit Read-Write Memory Ali Modarressi Abdullatif Köksal Ayyoob Imani Mohsen Fayyaz Hinrich Schütze KELM 91 9 0 17 Apr 2024
Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data Annotation Juhwan Choi Jungmin Yun Kyohoon Jin Youngbin Kim 17 3 0 15 Apr 2024
A Comprehensive Survey of Document-level Relation Extraction (2016-2023) Lea Demelius Hanh Thi Hong Tran Roman Kern Georgeta Bordea Andreas Trügler Antoine Doucet 8 3 0 28 Sep 2023
A Frustratingly Easy Improvement for Position Embeddings via Random Padding Mingxu Tao Yansong Feng Dongyan Zhao 16 6 0 08 May 2023
Data Augmentation using Pre-trained Transformer Models Varun Kumar Ashutosh Choudhary Eunah Cho VLM 206 315 0 04 Mar 2020
FewRel 2.0: Towards More Challenging Few-Shot Relation Classification Tianyu Gao Xu Han Hao Zhu Zhiyuan Liu Peng Li Maosong Sun Jie Zhou 192 221 0 16 Oct 2019