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. 2404.01701
  4. Cited By
On the Role of Summary Content Units in Text Summarization Evaluation

On the Role of Summary Content Units in Text Summarization Evaluation

2 April 2024
Marcel Nawrath
Agnieszka Nowak
Tristan Ratz
Danilo C. Walenta
Juri Opitz
Leonardo F. R. Ribeiro
João Sedoc
Daniel Deutsch
Simon Mille
Yixin Liu
Lining Zhang
Sebastian Gehrmann
Saad Mahamood
Miruna Clinciu
Khyathi Raghavi Chandu
Yufang Hou
    ELM
ArXivPDFHTML

Papers citing "On the Role of Summary Content Units in Text Summarization Evaluation"

6 / 6 papers shown
Title
QAPyramid: Fine-grained Evaluation of Content Selection for Text
  Summarization
QAPyramid: Fine-grained Evaluation of Content Selection for Text Summarization
Shiyue Zhang
David Wan
Arie Cattan
Ayal Klein
Ido Dagan
Joey Tianyi Zhou
86
0
0
10 Dec 2024
PARAPHRASUS : A Comprehensive Benchmark for Evaluating Paraphrase
  Detection Models
PARAPHRASUS : A Comprehensive Benchmark for Evaluating Paraphrase Detection Models
Andrianos Michail
Simon Clematide
Juri Opitz
29
3
0
18 Sep 2024
A Systematic Survey of Text Summarization: From Statistical Methods to
  Large Language Models
A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models
Haopeng Zhang
Philip S. Yu
Jiawei Zhang
37
17
0
17 Jun 2024
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
313
11,953
0
04 Mar 2022
Finding a Balanced Degree of Automation for Summary Evaluation
Finding a Balanced Degree of Automation for Summary Evaluation
Shiyue Zhang
Joey Tianyi Zhou
52
43
0
23 Sep 2021
Teaching Machines to Read and Comprehend
Teaching Machines to Read and Comprehend
Karl Moritz Hermann
Tomás Kociský
Edward Grefenstette
L. Espeholt
W. Kay
Mustafa Suleyman
Phil Blunsom
175
3,510
0
10 Jun 2015
1