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Large Language Models for Document-Level Event-Argument Data
  Augmentation for Challenging Role Types

Large Language Models for Document-Level Event-Argument Data Augmentation for Challenging Role Types

5 March 2024
Joseph Gatto
Parker Seegmiller
Omar Sharif
S. Preum
ArXivPDFHTML

Papers citing "Large Language Models for Document-Level Event-Argument Data Augmentation for Challenging Role Types"

2 / 2 papers shown
Title
Boosting Event Extraction with Denoised Structure-to-Text Augmentation
Boosting Event Extraction with Denoised Structure-to-Text Augmentation
Bo Wang
Heyan Huang
Xiaochi Wei
Ge Shi
Xiao Liu
Chong Feng
Tong Zhou
Shuai Wang
Dawei Yin
31
5
0
16 May 2023
GENEVA: Benchmarking Generalizability for Event Argument Extraction with
  Hundreds of Event Types and Argument Roles
GENEVA: Benchmarking Generalizability for Event Argument Extraction with Hundreds of Event Types and Argument Roles
Tanmay Parekh
I-Hung Hsu
Kuan-Hao Huang
Kai-Wei Chang
Nanyun Peng
38
25
0
25 May 2022
1