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FFCI: A Framework for Interpretable Automatic Evaluation of
  Summarization

FFCI: A Framework for Interpretable Automatic Evaluation of Summarization

27 November 2020
Fajri Koto
Timothy Baldwin
Jey Han Lau
    HILM
ArXivPDFHTML

Papers citing "FFCI: A Framework for Interpretable Automatic Evaluation of Summarization"

13 / 13 papers shown
Title
Summarization Metrics for Spanish and Basque: Do Automatic Scores and LLM-Judges Correlate with Humans?
Summarization Metrics for Spanish and Basque: Do Automatic Scores and LLM-Judges Correlate with Humans?
Jeremy Barnes
Naiara Perez
Alba Bonet-Jover
Begoña Altuna
59
1
0
21 Mar 2025
APPLS: Evaluating Evaluation Metrics for Plain Language Summarization
APPLS: Evaluating Evaluation Metrics for Plain Language Summarization
Yue Guo
Tal August
Gondy Leroy
T. Cohen
Lucy Lu Wang
55
9
0
23 May 2023
Just ClozE! A Novel Framework for Evaluating the Factual Consistency
  Faster in Abstractive Summarization
Just ClozE! A Novel Framework for Evaluating the Factual Consistency Faster in Abstractive Summarization
Yiyang Li
Lei Li
Marina Litvak
N. Vanetik
Dingxing Hu
Yuze Li
Yanquan Zhou
HILM
30
0
0
06 Oct 2022
Investigating Crowdsourcing Protocols for Evaluating the Factual
  Consistency of Summaries
Investigating Crowdsourcing Protocols for Evaluating the Factual Consistency of Summaries
Xiangru Tang
Alexander R. Fabbri
Haoran Li
Ziming Mao
Griffin Adams
Borui Wang
Asli Celikyilmaz
Yashar Mehdad
Dragomir R. Radev
HILM
13
19
0
19 Sep 2021
Evaluating the Efficacy of Summarization Evaluation across Languages
Evaluating the Efficacy of Summarization Evaluation across Languages
Fajri Koto
Jey Han Lau
Timothy Baldwin
42
19
0
02 Jun 2021
The Factual Inconsistency Problem in Abstractive Text Summarization: A
  Survey
The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey
Yi-Chong Huang
Xiachong Feng
Xiaocheng Feng
Bing Qin
HILM
128
104
0
30 Apr 2021
Understanding Factuality in Abstractive Summarization with FRANK: A
  Benchmark for Factuality Metrics
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics
Artidoro Pagnoni
Vidhisha Balachandran
Yulia Tsvetkov
HILM
222
305
0
27 Apr 2021
Factual Error Correction for Abstractive Summarization Models
Factual Error Correction for Abstractive Summarization Models
Mengyao Cao
Yue Dong
Jiapeng Wu
Jackie C.K. Cheung
HILM
KELM
169
159
0
17 Oct 2020
Exploring Content Selection in Summarization of Novel Chapters
Exploring Content Selection in Summarization of Novel Chapters
Faisal Ladhak
Bryan Li
Yaser Al-Onaizan
Kathleen McKeown
61
35
0
04 May 2020
Discrete Optimization for Unsupervised Sentence Summarization with
  Word-Level Extraction
Discrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction
Raphael Schumann
Lili Mou
Yao Lu
Olga Vechtomova
K. Markert
183
41
0
04 May 2020
On Extractive and Abstractive Neural Document Summarization with
  Transformer Language Models
On Extractive and Abstractive Neural Document Summarization with Transformer Language Models
Sandeep Subramanian
Raymond Li
Jonathan Pilault
C. Pal
233
215
0
07 Sep 2019
Text Summarization with Pretrained Encoders
Text Summarization with Pretrained Encoders
Yang Liu
Mirella Lapata
MILM
254
1,431
0
22 Aug 2019
Detecting (Un)Important Content for Single-Document News Summarization
Detecting (Un)Important Content for Single-Document News Summarization
Yinfei Yang
F. S. Bao
A. Nenkova
19
18
0
26 Feb 2017
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