ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2104.13579
  4. Cited By
Multi-view Inference for Relation Extraction with Uncertain Knowledge

Multi-view Inference for Relation Extraction with Uncertain Knowledge

28 April 2021
Bo Li
Wei Ye
Canming Huang
Shikun Zhang
ArXivPDFHTML

Papers citing "Multi-view Inference for Relation Extraction with Uncertain Knowledge"

7 / 7 papers shown
Title
Rethinking Document-Level Relation Extraction: A Reality Check
Rethinking Document-Level Relation Extraction: A Reality Check
Jing Li
Yequan Wang
Shuai Zhang
Min Zhang
19
12
0
15 Jun 2023
Towards Integration of Discriminability and Robustness for
  Document-Level Relation Extraction
Towards Integration of Discriminability and Robustness for Document-Level Relation Extraction
Jiannan Guo
Stanley Kok
Lidong Bing
16
8
0
03 Apr 2023
Reviewing Labels: Label Graph Network with Top-k Prediction Set for
  Relation Extraction
Reviewing Labels: Label Graph Network with Top-k Prediction Set for Relation Extraction
Bo Li
Wei Ye
Jinglei Zhang
Shikun Zhang
18
12
0
29 Dec 2022
Sequence Generation with Label Augmentation for Relation Extraction
Sequence Generation with Label Augmentation for Relation Extraction
Bo Li
Dingyao Yu
Wei Ye
Jinglei Zhang
Shikun Zhang
VLM
31
18
0
29 Dec 2022
ConstGCN: Constrained Transmission-based Graph Convolutional Networks
  for Document-level Relation Extraction
ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction
Ji Qi
Bin Xu
Kaisheng Zeng
Jinxin Liu
Jifan Yu
Qifang Gao
Juanzi Li
Lei Hou
GNN
8
1
0
08 Oct 2022
REKnow: Enhanced Knowledge for Joint Entity and Relation Extraction
REKnow: Enhanced Knowledge for Joint Entity and Relation Extraction
Sheng Zhang
Patrick K. L. Ng
Zhiguo Wang
Bing Xiang
11
4
0
10 Jun 2022
Coarse-to-Fine Entity Representations for Document-level Relation
  Extraction
Coarse-to-Fine Entity Representations for Document-level Relation Extraction
Damai Dai
Jingjing Ren
Shuang Zeng
Baobao Chang
Zhifang Sui
AI4TS
6
3
0
04 Dec 2020
1