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Training on Synthetic Data Beats Real Data in Multimodal Relation
  Extraction

Training on Synthetic Data Beats Real Data in Multimodal Relation Extraction

5 December 2023
Zilin Du
Haoxin Li
Xu Guo
Boyang Li
ArXiv (abs)PDFHTML

Papers citing "Training on Synthetic Data Beats Real Data in Multimodal Relation Extraction"

23 / 73 papers shown
Title
How does Early Stopping Help Generalization against Label Noise?
How does Early Stopping Help Generalization against Label Noise?
Hwanjun Song
Minseok Kim
Dongmin Park
Jae-Gil Lee
NoLa
85
76
0
19 Nov 2019
FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
Tianyu Gao
Xu Han
Hao Zhu
Zhiyuan Liu
Peng Li
Maosong Sun
Jie Zhou
261
247
0
16 Oct 2019
RandAugment: Practical automated data augmentation with a reduced search
  space
RandAugment: Practical automated data augmentation with a reduced search space
E. D. Cubuk
Barret Zoph
Jonathon Shlens
Quoc V. Le
MQ
258
3,505
0
30 Sep 2019
Addressing Semantic Drift in Question Generation for Semi-Supervised
  Question Answering
Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering
Shiyue Zhang
Joey Tianyi Zhou
72
139
0
13 Sep 2019
VisualBERT: A Simple and Performant Baseline for Vision and Language
VisualBERT: A Simple and Performant Baseline for Vision and Language
Liunian Harold Li
Mark Yatskar
Da Yin
Cho-Jui Hsieh
Kai-Wei Chang
VLM
153
1,965
0
09 Aug 2019
On Variational Bounds of Mutual Information
On Variational Bounds of Mutual Information
Ben Poole
Sherjil Ozair
Aaron van den Oord
Alexander A. Alemi
George Tucker
SSL
111
814
0
16 May 2019
Entity-Relation Extraction as Multi-Turn Question Answering
Entity-Relation Extraction as Multi-Turn Question Answering
Xiaoya Li
Fan Yin
Zijun Sun
Xiayu Li
Arianna Yuan
Duo Chai
Mingxin Zhou
Jiwei Li
78
347
0
14 May 2019
Understanding and Utilizing Deep Neural Networks Trained with Noisy
  Labels
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
Pengfei Chen
B. Liao
Guangyong Chen
Shengyu Zhang
NoLa
74
388
0
13 May 2019
The Curious Case of Neural Text Degeneration
The Curious Case of Neural Text Degeneration
Ari Holtzman
Jan Buys
Li Du
Maxwell Forbes
Yejin Choi
199
3,211
0
22 Apr 2019
Gradient Descent with Early Stopping is Provably Robust to Label Noise
  for Overparameterized Neural Networks
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks
Mingchen Li
Mahdi Soltanolkotabi
Samet Oymak
NoLa
107
353
0
27 Mar 2019
How does Disagreement Help Generalization against Label Corruption?
How does Disagreement Help Generalization against Label Corruption?
Xingrui Yu
Bo Han
Jiangchao Yao
Gang Niu
Ivor W. Tsang
Masashi Sugiyama
NoLa
76
787
0
14 Jan 2019
Formal Limitations on the Measurement of Mutual Information
Formal Limitations on the Measurement of Mutual Information
David A. McAllester
K. Stratos
SSL
72
277
0
10 Nov 2018
Learning deep representations by mutual information estimation and
  maximization
Learning deep representations by mutual information estimation and maximization
R. Devon Hjelm
A. Fedorov
Samuel Lavoie-Marchildon
Karan Grewal
Phil Bachman
Adam Trischler
Yoshua Bengio
SSLDRL
348
2,672
0
20 Aug 2018
Representation Learning with Contrastive Predictive Coding
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord
Yazhe Li
Oriol Vinyals
DRLSSL
351
10,364
0
10 Jul 2018
Women also Snowboard: Overcoming Bias in Captioning Models (Extended
  Abstract)
Women also Snowboard: Overcoming Bias in Captioning Models (Extended Abstract)
Lisa Anne Hendricks
Kaylee Burns
Kate Saenko
Trevor Darrell
Anna Rohrbach
123
480
0
02 Jul 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely
  Noisy Labels
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
Bo Han
Quanming Yao
Xingrui Yu
Gang Niu
Miao Xu
Weihua Hu
Ivor Tsang
Masashi Sugiyama
NoLa
120
2,078
0
18 Apr 2018
Training Deep Networks with Synthetic Data: Bridging the Reality Gap by
  Domain Randomization
Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization
Jonathan Tremblay
Aayush Prakash
David Acuna
M. Brophy
Varun Jampani
Cem Anil
Thang To
Eric Cameracci
Shaad Boochoon
Stan Birchfield
OOD
84
818
0
18 Apr 2018
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks
  on Corrupted Labels
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang
Zhengyuan Zhou
Thomas Leung
Li Li
Li Fei-Fei
NoLa
128
1,456
0
14 Dec 2017
On Pre-Trained Image Features and Synthetic Images for Deep Learning
On Pre-Trained Image Features and Synthetic Images for Deep Learning
Stefan Hinterstoißer
Vincent Lepetit
Paul Wohlhart
K. Konolige
VLMObjD
47
230
0
29 Oct 2017
A Closer Look at Memorization in Deep Networks
A Closer Look at Memorization in Deep Networks
Devansh Arpit
Stanislaw Jastrzebski
Nicolas Ballas
David M. Krueger
Emmanuel Bengio
...
Tegan Maharaj
Asja Fischer
Aaron Courville
Yoshua Bengio
Simon Lacoste-Julien
TDI
128
1,825
0
16 Jun 2017
Decoupling "when to update" from "how to update"
Decoupling "when to update" from "how to update"
Eran Malach
Shai Shalev-Shwartz
NoLa
97
568
0
08 Jun 2017
Driving in the Matrix: Can Virtual Worlds Replace Human-Generated
  Annotations for Real World Tasks?
Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?
Matthew Johnson-Roberson
Charlie Barto
Rounak Mehta
S. N. Sridhar
Karl Rosaen
Ram Vasudevan
117
617
0
06 Oct 2016
WikiReading: A Novel Large-scale Language Understanding Task over
  Wikipedia
WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia
D. Hewlett
Alexandre Lacoste
Llion Jones
Illia Polosukhin
Andrew Fandrianto
Jay Han
Matthew Kelcey
David Berthelot
RALM
67
139
0
11 Aug 2016
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