Fetching the paper…
Reading the bibliography…
Fact Verification requires fine-grained natural language inference capability that finds subtle clues to identify the syntactical and semantically correct but not well-supported claims.
Tianda Li, Xiaodan Zhu, Quan Liu, Qian Chen, Zhigang Chen, and Si Wei. 2019 · 1904
Earlier work this paper cites.
Understanding the behaviors of bert in ranking
Yifan Qiao, Chenyan Xiong, Zhenghao Liu, and Zhiyuan Liu. 2019 · 1904
Earlier work this paper cites.
Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Reasoning over semantic-level graph for fact checking
Wanjun Zhong, Jingjing Xu, Duyu Tang, Zenan Xu, Nan Duan, Ming Zhou, Jiahai Wang, and Jian Yin. 2019 · 1909
Earlier work this paper cites.
BERT for evidence retrieval and claim verification
Amir Soleimani, Christof Monz, and Marcel Worring. 2019 · 1910
Earlier work this paper cites.
Coreferential reasoning learning for language representation
Deming Ye, Yankai Lin, Jiaju Du, Zhenghao Liu, Maosong Sun, and Zhiyuan Liu. 2020 · 2004
Earlier work this paper cites.
The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. 2008 · 2008
Earlier work this paper cites.
A deep relevance matching model for ad-hoc retrieval
Jiafeng Guo, Yixing Fan, Qingyao Ai, and W.Bruce Croft. 2016 · 2016
Earlier work this paper cites.
Text matching as image recognition
Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, Shengxian Wan, and Xueqi Cheng. 2016 · 2016
Earlier work this paper cites.
A decomposable attention model for natural language inference
Ankur Parikh, Oscar Täckström, Dipanjan Das, and Jakob Uszkoreit. 2016 · 2016
Earlier work this paper cites.
Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling. 2017 · 2017
Earlier work this paper cites.
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017 · 2017
Cited alongside, same era.
End-to-end neural ad-hoc ranking with kernel pooling
Chenyan Xiong, Zhuyun Dai, Jamie Callan, Zhiyuan Liu, and Russell Power. 2017 · 2017
Cited alongside, same era.
Convolutional neural networks for soft-matching n-grams in ad-hoc search
Zhuyun Dai, Chenyan Xiong, Jamie Callan, and Zhiyuan Liu. 2018 · 2018
Cited alongside, same era.
AllenNLP: A deep semantic natural language processing platform
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson F Liu, Matthew Peters, Michael Schmitz, and Luke Zettlemoyer. 2018 · 2018
Cited alongside, same era.
Dr-bilstm: Dependent reading bidirectional LSTM for natural language inference
Reza Ghaeini, Sadid A Hasan, Vivek Datla, Joey Liu, Kathy Lee, Ashequl Qadir, Yuan Ling, Aaditya Prakash, Xiaoli Fern, and Oladimeji Farri. 2018 · 2018
Cited alongside, same era.
UCL machine reading group: Four factor framework for fact finding (HexaF)
Takuma Yoneda, Jeff Mitchell, Johannes Welbl, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
Later among the works it cites.
What does BERT look at? an analysis of BERT’s attention
Kevin Clark, Urvashi Khandelwal, Omer Levy, and Christopher D Manning. 2019 · 2019
Closest in time.
Deeper text understanding for ir with contextual neural language modeling
Zhuyun Dai and Jamie Callan. 2019 · 2019
Closest in time.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Closest in time.
Understanding attention and generalization in graph neural networks
Boris Knyazev, Graham W Taylor, and Mohamed R Amer. 2019 · 2019
Closest in time.
CEDR: contextualized embeddings for document ranking
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
UKP-athene: Multi-sentence textual entailment for claim verification
Andreas Hanselowski, Hao Zhang, Zile Li, Daniil Sorokin, Benjamin Schiller, Claudia Schulz, and Iryna Gurevych. 2018 · 2018
Cited alongside, same era.
QED: A fact verification system for the fever shared task
Jackson Luken, Nanjiang Jiang, and Marie-Catherine de Marneffe. 2018 · 2018
Cited alongside, same era.
Deep contextualized word representations
Matthew E Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Cited alongside, same era.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
Cited alongside, same era.
TwoWingOS: A two-wing optimization strategy for evidential claim verification
Wenpeng Yin and Dan Roth. 2018 · 2018
Cited alongside, same era.
Reading wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017a
Cited in the paper.
Enhanced LSTM for natural language inference
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Si Wei, Hui Jiang, and Diana Inkpen. 2017b
Cited in the paper.
Sean MacAvaney, Andrew Yates, Arman Cohan, and Nazli Goharian. 2019 · 2019
Closest in time.
Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V Le. 2019 · 2019
Closest in time.
GEAR: Graph-based evidence aggregating and reasoning for fact verification
Jie Zhou, Xu Han, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li, and Maosong Sun. 2019 · 2019
Closest in time.
Transformer-xh: Multi-evidence reasoning with extra hop attention
Chen Zhao, Chenyan Xiong, Corby Rosset, Xia Song, Paul Bennett, and Saurabh Tiwary. 2020 · 2020
Closest in time.
Convolutional neural network architectures for matching natural language sentences
Baotian Hu, Zhengdong Lu, Hang Li, and Qingcai Chen. 2014 · 2050
Closest in time.