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Handling Divergent Reference Texts when Evaluating Table-to-Text
  Generation

Handling Divergent Reference Texts when Evaluating Table-to-Text Generation

3 June 2019
Bhuwan Dhingra
Manaal Faruqui
Ankur P. Parikh
Ming-Wei Chang
Dipanjan Das
William W. Cohen
ArXivPDFHTML

Papers citing "Handling Divergent Reference Texts when Evaluating Table-to-Text Generation"

25 / 125 papers shown
Title
The GEM Benchmark: Natural Language Generation, its Evaluation and
  Metrics
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Sebastian Gehrmann
Tosin Adewumi
Karmanya Aggarwal
Pawan Sasanka Ammanamanchi
Aremu Anuoluwapo
...
Nishant Subramani
Wei Xu
Diyi Yang
Akhila Yerukola
Jiawei Zhou
VLM
260
285
0
02 Feb 2021
Data-to-text Generation by Splicing Together Nearest Neighbors
Data-to-text Generation by Splicing Together Nearest Neighbors
Sam Wiseman
A. Backurs
K. Stratos
27
9
0
20 Jan 2021
What Makes Good In-Context Examples for GPT-$3$?
What Makes Good In-Context Examples for GPT-333?
Jiachang Liu
Dinghan Shen
Yizhe Zhang
Bill Dolan
Lawrence Carin
Weizhu Chen
AAML
RALM
275
1,313
0
17 Jan 2021
WikiTableT: A Large-Scale Data-to-Text Dataset for Generating Wikipedia
  Article Sections
WikiTableT: A Large-Scale Data-to-Text Dataset for Generating Wikipedia Article Sections
Mingda Chen
Sam Wiseman
Kevin Gimpel
27
30
0
29 Dec 2020
Denoising Pre-Training and Data Augmentation Strategies for Enhanced RDF
  Verbalization with Transformers
Denoising Pre-Training and Data Augmentation Strategies for Enhanced RDF Verbalization with Transformers
Sébastien Montella
Betty Fabre
Tanguy Urvoy
Johannes Heinecke
L. Rojas-Barahona
26
14
0
01 Dec 2020
A Gold Standard Methodology for Evaluating Accuracy in Data-To-Text
  Systems
A Gold Standard Methodology for Evaluating Accuracy in Data-To-Text Systems
Craig Thomson
Ehud Reiter
22
52
0
08 Nov 2020
PARENTing via Model-Agnostic Reinforcement Learning to Correct
  Pathological Behaviors in Data-to-Text Generation
PARENTing via Model-Agnostic Reinforcement Learning to Correct Pathological Behaviors in Data-to-Text Generation
Clément Rebuffel
Laure Soulier
Geoffrey Scoutheeten
Patrick Gallinari
8
9
0
21 Oct 2020
Controlled Hallucinations: Learning to Generate Faithfully from Noisy
  Data
Controlled Hallucinations: Learning to Generate Faithfully from Noisy Data
Katja Filippova
21
106
0
12 Oct 2020
A Survey of Evaluation Metrics Used for NLG Systems
A Survey of Evaluation Metrics Used for NLG Systems
Ananya B. Sai
Akash Kumar Mohankumar
Mitesh M. Khapra
ELM
33
230
0
27 Aug 2020
Evaluating for Diversity in Question Generation over Text
Evaluating for Diversity in Question Generation over Text
M. Schlichtkrull
Weiwei Cheng
16
5
0
17 Aug 2020
DART: Open-Domain Structured Data Record to Text Generation
DART: Open-Domain Structured Data Record to Text Generation
Linyong Nan
Dragomir R. Radev
Rui Zhang
Amrit Rau
Abhinand Sivaprasad
...
Y. Tan
Xi Lin
Caiming Xiong
R. Socher
Nazneen Rajani
12
199
0
06 Jul 2020
Text-to-Text Pre-Training for Data-to-Text Tasks
Text-to-Text Pre-Training for Data-to-Text Tasks
Mihir Kale
Abhinav Rastogi
AI4CE
19
200
0
21 May 2020
INFOTABS: Inference on Tables as Semi-structured Data
INFOTABS: Inference on Tables as Semi-structured Data
Vivek Gupta
Maitrey Mehta
Pegah Nokhiz
Vivek Srikumar
LMTD
25
100
0
13 May 2020
Towards Faithful Neural Table-to-Text Generation with Content-Matching
  Constraints
Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints
Zhenyi Wang
Xiaoyang Wang
Bang An
Dong Yu
Changyou Chen
LMTD
168
84
0
03 May 2020
On Faithfulness and Factuality in Abstractive Summarization
On Faithfulness and Factuality in Abstractive Summarization
Joshua Maynez
Shashi Narayan
Bernd Bohnet
Ryan T. McDonald
HILM
28
1,001
0
02 May 2020
ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
Liying Cheng
Dekun Wu
Lidong Bing
Yan Zhang
Zhanming Jie
Wei Lu
Luo Si
3DV
24
2
0
30 Apr 2020
Improved Natural Language Generation via Loss Truncation
Improved Natural Language Generation via Loss Truncation
Daniel Kang
Tatsunori Hashimoto
25
97
0
30 Apr 2020
Logic2Text: High-Fidelity Natural Language Generation from Logical Forms
Logic2Text: High-Fidelity Natural Language Generation from Logical Forms
Zhiyu Zoey Chen
Wenhu Chen
Hanwen Zha
Xiyou Zhou
Yunkai Zhang
Sairam Sundaresan
William Yang Wang
NAI
24
64
0
30 Apr 2020
ToTTo: A Controlled Table-To-Text Generation Dataset
ToTTo: A Controlled Table-To-Text Generation Dataset
Ankur P. Parikh
Xuezhi Wang
Sebastian Gehrmann
Manaal Faruqui
Bhuwan Dhingra
Diyi Yang
Dipanjan Das
LMTD
32
352
0
29 Apr 2020
Logical Natural Language Generation from Open-Domain Tables
Logical Natural Language Generation from Open-Domain Tables
Wenhu Chen
Jianshu Chen
Yunde Su
Zhiyu Zoey Chen
William Yang Wang
LMTD
34
155
0
22 Apr 2020
Optimizing the Factual Correctness of a Summary: A Study of Summarizing
  Radiology Reports
Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports
Yuhao Zhang
Derek Merck
E. Tsai
Christopher D. Manning
C. Langlotz
MedIm
HILM
27
185
0
06 Nov 2019
Sticking to the Facts: Confident Decoding for Faithful Data-to-Text
  Generation
Sticking to the Facts: Confident Decoding for Faithful Data-to-Text Generation
Ran Tian
Shashi Narayan
Thibault Sellam
Ankur P. Parikh
HILM
25
94
0
19 Oct 2019
Few-Shot NLG with Pre-Trained Language Model
Few-Shot NLG with Pre-Trained Language Model
Zhiyu Zoey Chen
H. Eavani
Wenhu Chen
Yinyin Liu
William Yang Wang
LMTD
22
141
0
21 Apr 2019
Bootstrapping Generators from Noisy Data
Bootstrapping Generators from Noisy Data
Laura Perez-Beltrachini
Mirella Lapata
28
40
0
17 Apr 2018
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Zhehuai Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
718
6,750
0
26 Sep 2016
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