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. 2001.00725
  4. Cited By
TED: A Pretrained Unsupervised Summarization Model with Theme Modeling
  and Denoising

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising

3 January 2020
Ziyi Yang
Chenguang Zhu
R. Gmyr
Michael Zeng
Xuedong Huang
Eric Darve
ArXivPDFHTML

Papers citing "TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising"

13 / 13 papers shown
Title
Query-Guided Self-Supervised Summarization of Nursing Notes
Query-Guided Self-Supervised Summarization of Nursing Notes
Ya Gao
H. Moen
S. Koivusalo
M. Koskinen
Pekka Marttinen
44
1
0
04 Jul 2024
A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methods
A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methods
Hanlei Jin
Yang Zhang
Dan Meng
Jun Wang
Jinghua Tan
68
80
0
05 Mar 2024
Unsupervised Extractive Summarization with Learnable Length Control
  Strategies
Unsupervised Extractive Summarization with Learnable Length Control Strategies
Renlong Jie
Xiaojun Meng
Xin Jiang
Qun Liu
32
1
0
12 Dec 2023
RTSUM: Relation Triple-based Interpretable Summarization with
  Multi-level Salience Visualization
RTSUM: Relation Triple-based Interpretable Summarization with Multi-level Salience Visualization
Seonglae Cho
Yonggi Cho
HoonJae Lee
Myungha Jang
Jinyoung Yeo
Dongha Lee
27
0
0
21 Oct 2023
i-Code V2: An Autoregressive Generation Framework over Vision, Language,
  and Speech Data
i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
Ziyi Yang
Mahmoud Khademi
Yichong Xu
Reid Pryzant
Yuwei Fang
...
Yu Shi
Lu Yuan
Takuya Yoshioka
Michael Zeng
Xuedong Huang
17
2
0
21 May 2023
Combining State-of-the-Art Models with Maximal Marginal Relevance for
  Few-Shot and Zero-Shot Multi-Document Summarization
Combining State-of-the-Art Models with Maximal Marginal Relevance for Few-Shot and Zero-Shot Multi-Document Summarization
David Adams
Gandharv Suri
Yllias Chali
VLM
26
3
0
19 Nov 2022
Towards Summary Candidates Fusion
Towards Summary Candidates Fusion
Mathieu Ravaut
Chenyu You
Nancy F. Chen
32
14
0
17 Oct 2022
Learning Non-Autoregressive Models from Search for Unsupervised Sentence
  Summarization
Learning Non-Autoregressive Models from Search for Unsupervised Sentence Summarization
Puyuan Liu
Chenyang Huang
Lili Mou
32
20
0
28 May 2022
PSP: Pre-trained Soft Prompts for Few-Shot Abstractive Summarization
PSP: Pre-trained Soft Prompts for Few-Shot Abstractive Summarization
Xiaochen Liu
Yang Gao
Yu Bai
Jiawei Li
Yinan Hu
Yang Gao
Boxing Chen
40
22
0
09 Apr 2022
Unsupervised Multi-Granularity Summarization
Unsupervised Multi-Granularity Summarization
Ming Zhong
Yang Liu
Suyu Ge
Yuning Mao
Yizhu Jiao
Xingxing Zhang
Yichong Xu
Chenguang Zhu
Michael Zeng
Jiawei Han
87
8
0
29 Jan 2022
Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source
  Pretraining
Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source Pretraining
Yicheng Zou
Bolin Zhu
Xingwu Hu
Tao Gui
Qi Zhang
86
32
0
09 Sep 2021
Neural Rule-Execution Tracking Machine For Transformer-Based Text
  Generation
Neural Rule-Execution Tracking Machine For Transformer-Based Text Generation
Yufei Wang
Can Xu
Huang Hu
Chongyang Tao
Stephen Wan
Mark Dras
Mark Johnson
Daxin Jiang
19
10
0
27 Jul 2021
Text Summarization with Pretrained Encoders
Text Summarization with Pretrained Encoders
Yang Liu
Mirella Lapata
MILM
258
1,433
0
22 Aug 2019
1