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. 2010.04141
  4. Cited By
DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool

DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool

8 October 2020
Ernie Chang
J. Caplinger
Alex Marin
Xiaoyu Shen
Vera Demberg
ArXivPDFHTML

Papers citing "DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool"

3 / 3 papers shown
Title
EASE: An Easily-Customized Annotation System Powered by Efficiency
  Enhancement Mechanisms
EASE: An Easily-Customized Annotation System Powered by Efficiency Enhancement Mechanisms
Naihao Deng
Yikai Liu
Mingye Chen
Winston Wu
Siyang Liu
Yulong Chen
Yue Zhang
Rada Mihalcea
39
0
0
23 May 2023
LOGEN: Few-shot Logical Knowledge-Conditioned Text Generation with
  Self-training
LOGEN: Few-shot Logical Knowledge-Conditioned Text Generation with Self-training
Shumin Deng
Jiacheng Yang
Hongbin Ye
Chuanqi Tan
Mosha Chen
Songfang Huang
Fei Huang
Huajun Chen
Ningyu Zhang
27
7
0
02 Dec 2021
On Training Instance Selection for Few-Shot Neural Text Generation
On Training Instance Selection for Few-Shot Neural Text Generation
Ernie Chang
Xiaoyu Shen
Hui-Syuan Yeh
Vera Demberg
38
40
0
07 Jul 2021
1