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A Multi-Level Attention Model for Evidence-Based Fact Checking

A Multi-Level Attention Model for Evidence-Based Fact Checking

2 June 2021
Canasai Kruengkrai
Junichi Yamagishi
Xin Wang
    GNN
ArXivPDFHTML

Papers citing "A Multi-Level Attention Model for Evidence-Based Fact Checking"

6 / 6 papers shown
Title
Internet-augmented language models through few-shot prompting for
  open-domain question answering
Internet-augmented language models through few-shot prompting for open-domain question answering
Angeliki Lazaridou
E. Gribovskaya
Wojciech Stokowiec
N. Grigorev
KELM
LRM
20
132
0
10 Mar 2022
Synthetic Disinformation Attacks on Automated Fact Verification Systems
Synthetic Disinformation Attacks on Automated Fact Verification Systems
Y. Du
Antoine Bosselut
Christopher D. Manning
AAML
OffRL
36
32
0
18 Feb 2022
Robust Deepfake On Unrestricted Media: Generation And Detection
Robust Deepfake On Unrestricted Media: Generation And Detection
Trung-Nghia Le
H. Nguyen
Junichi Yamagishi
Isao Echizen
36
7
0
13 Feb 2022
Revealing the Importance of Semantic Retrieval for Machine Reading at
  Scale
Revealing the Importance of Semantic Retrieval for Machine Reading at Scale
Yixin Nie
Songhe Wang
Joey Tianyi Zhou
RALM
164
134
0
17 Sep 2019
Reasoning Over Semantic-Level Graph for Fact Checking
Reasoning Over Semantic-Level Graph for Fact Checking
Wanjun Zhong
Jingjing Xu
Duyu Tang
Zenan Xu
Nan Duan
M. Zhou
Jiahai Wang
Jian Yin
HILM
GNN
185
166
0
09 Sep 2019
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,640
0
03 Jul 2012
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