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. 2309.04977
  4. Cited By
RGAT: A Deeper Look into Syntactic Dependency Information for
  Coreference Resolution

RGAT: A Deeper Look into Syntactic Dependency Information for Coreference Resolution

10 September 2023
Yuan Meng
Xuhao Pan
Jun Chang
Yue Wang
ArXivPDFHTML

Papers citing "RGAT: A Deeper Look into Syntactic Dependency Information for Coreference Resolution"

3 / 3 papers shown
Title
LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of
  Large Language Models
LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models
Zhiqiang Hu
Lei Wang
Yihuai Lan
Wanyu Xu
Ee-Peng Lim
Lidong Bing
Xing Xu
Soujanya Poria
Roy Ka-wei Lee
ALM
81
249
0
04 Apr 2023
Higher-order Coreference Resolution with Coarse-to-fine Inference
Higher-order Coreference Resolution with Coarse-to-fine Inference
Kenton Lee
Luheng He
Luke Zettlemoyer
BDL
69
469
0
15 Apr 2018
Modeling Relational Data with Graph Convolutional Networks
Modeling Relational Data with Graph Convolutional Networks
Michael Schlichtkrull
Thomas Kipf
Peter Bloem
Rianne van den Berg
Ivan Titov
Max Welling
GNN
172
4,772
0
17 Mar 2017
1