Fetching the paper…
Reading the bibliography…
Stance detection concerns the classification of a writer's viewpoint towards a target.
Multi-task learning of pairwise sequence classification tasks over disparate label spaces
Isabelle Augenstein, Sebastian Ruder, and Anders Søgaard. 2018 · 1906
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.
The argument reasoning comprehension task: Identification and reconstruction of implicit warrants
Ivan Habernal, Henning Wachsmuth, Iryna Gurevych, and Benno Stein. 2018 · 1940
Earlier work this paper cites.
NLTK: The natural language toolkit
Edward Loper and Steven Bird. 2002 · 2002
Earlier work this paper cites.
Domain adaptation with structural correspondence learning
John Blitzer, Ryan McDonald, and Fernando Pereira. 2006 · 2006
Earlier work this paper cites.
Frustratingly easy domain adaptation
Hal Daumé III. 2007 · 2007
Earlier work this paper cites.
Visualizing data using t-SNE
Laurens van der Maaten and Geoffrey Hinton. 2008 · 2008
Earlier work this paper cites.
Hierarchical Bayesian domain adaptation
Jenny Rose Finkel and Christopher D. Manning. 2009 · 2009
Earlier work this paper cites.
Recognizing stances in online debates
Swapna Somasundaran and Janyce Wiebe. 2009 · 2009
Earlier work this paper cites.
Data-efficient pretraining via contrastive self-supervision
Nils Rethmeier and Isabelle Augenstein. 2020 · 2010
Earlier work this paper cites.
Recognizing stances in ideological on-line debates
Swapna Somasundaran and Janyce Wiebe. 2010 · 2010
Earlier work this paper cites.
Rumor has it: Identifying misinformation in microblogs
Vahed Qazvinian, Emily Rosengren, Dragomir R. Radev, and Qiaozhu Mei. 2011 · 2011
Earlier work this paper cites.
A corpus for research on deliberation and debate
Marilyn Walker, Jean Fox Tree, Pranav Anand, Rob Abbott, and Joseph King. 2012 · 2012
Earlier work this paper cites.
Semi-supervised domain adaptation with instance constraints
Jeff Donahue, Judy Hoffman, Erik Rodner, Kate Saenko, and Trevor Darrell. 2013 · 2013
Earlier work this paper cites.
Stance classification of ideological debates: Data, models, features, and constraints
Kazi Saidul Hasan and Vincent Ng. 2013 · 2013
Earlier work this paper cites.
A benchmark dataset for automatic detection of claims and evidence in the context of controversial topics
Ehud Aharoni, Anatoly Polnarov, Tamar Lavee, Daniel Hershcovich, Ran Levy, Ruty Rinott, Dan Gutfreund, and Noam Slonim. 2014 · 2014
Earlier work this paper cites.
Back up your stance: Recognizing arguments in online discussions
Filip Boltužić and Jan Šnajder. 2014 · 2014
Earlier work this paper cites.
Why are you taking this stance? Identifying and classifying reasons in ideological debates
Kazi Saidul Hasan and Vincent Ng. 2014 · 2014
Earlier work this paper cites.
GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Earlier work this paper cites.
Learning sentiment-specific word embedding for Twitter sentiment classification
Duyu Tang, Furu Wei, Nan Yang, Ming Zhou, Ting Liu, and Bing Qin. 2014 · 2014
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor S. Lempitsky. 2015 · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
From argumentation mining to stance classification
Parinaz Sobhani, Diana Inkpen, and Stan Matwin. 2015 · 2015
Earlier work this paper cites.
Semi-supervised domain adaptation with subspace learning for visual recognition
Ting Yao, Yingwei Pan, Chong-Wah Ngo, Houqiang Li, and Tao Mei. 2015 · 2015
Earlier work this paper cites.
Stance detection with bidirectional conditional encoding
Isabelle Augenstein, Tim Rocktäschel, Andreas Vlachos, and Kalina Bontcheva. 2016 · 2016
Earlier work this paper cites.
Emergent: a novel data-set for stance classification
William Ferreira and Andreas Vlachos. 2016 · 2016
Earlier work this paper cites.
SemEval-2016 task 6: Detecting stance in tweets
Saif Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016 · 2016
Earlier work this paper cites.
How transferable are neural networks in NLP applications?
Lili Mou, Zhao Meng, Rui Yan, Ge Li, Yan Xu, Lu Zhang, and Zhi Jin. 2016 · 2016
Cited alongside, same era.
Stance classification of context-dependent claims
Roy Bar-Haim, Indrajit Bhattacharya, Francesco Dinuzzo, Amrita Saha, and Noam Slonim. 2017 · 2017
Cited alongside, same era.
Part-of-speech tagging for Twitter with adversarial neural networks
Tao Gui, Qi Zhang, Haoran Huang, Minlong Peng, and Xuanjing Huang. 2017 · 2017
Cited alongside, same era.
Bag of tricks for efficient text classification
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2017 · 2017
Cited alongside, same era.
Stance and sentiment in tweets
Saif M. Mohammad, Parinaz Sobhani, and Svetlana Kiritchenko. 2017 · 2017
Cited alongside, same era.
PyTorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2017
Unsupervised domain adaptation of contextualized embeddings for sequence labeling
Xiaochuang Han and Jacob Eisenstein. 2019 · 2019
Later among the works it cites.
A richly annotated corpus for different tasks in automated fact-checking
Andreas Hanselowski, Christian Stab, Claudia Schulz, Zile Li, and Iryna Gurevych. 2019 · 2019
Later among the works it cites.
Domain adaptation with BERT-based domain classification and data selection
Xiaofei Ma, Peng Xu, Zhiguo Wang, Ramesh Nallapati, and Bing Xiang. 2019 · 2019
Later among the works it cites.
Contrastive language adaptation for cross-lingual stance detection
Mitra Mohtarami, James Glass, and Preslav Nakov. 2019 · 2019
Later among the works it cites.
GILE: A generalized input-label embedding for text classification
Nikolaos Pappas and James Henderson. 2019 · 2019
Later among the works it cites.
Energy and policy considerations for deep learning in NLP
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Fake news challenge stage 1 (FNC-I): Stance detection
Dean Pomerleau and Delip Rao. 2017 · 2017
Cited alongside, same era.
A dataset for multi-target stance detection
Parinaz Sobhani, Diana Inkpen, and Xiaodan Zhu. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Integrating stance detection and fact checking in a unified corpus
Ramy Baly, Mitra Mohtarami, James Glass, Lluís Màrquez, Alessandro Moschitti, and Preslav Nakov. 2018 · 2018
Cited alongside, same era.
Multi-source domain adaptation with mixture of experts
Jiang Guo, Darsh Shah, and Regina Barzilay. 2018 · 2018
Cited alongside, same era.
A retrospective analysis of the fake news challenge stance-detection task
Andreas Hanselowski, Avinesh PVS, Benjamin Schiller, Felix Caspelherr, Debanjan Chaudhuri, Christian M. Meyer, and Iryna Gurevych. 2018 · 2018
Cited alongside, same era.
Emma Strubell, Ananya Ganesh, and Andrew McCallum. 2019 · 2019
Later among the works it cites.
A survey on opinion mining: From stance to product aspect
Rui Wang, Deyu Zhou, Mingmin Jiang, Jiasheng Si, and Y. Yang. 2019 · 2019
Later among the works it cites.
Zero-Shot Stance Detection: A Dataset and Model using Generalized Topic Representations
Emily Allaway and Kathleen McKeown. 2020 · 2020
Later among the works it cites.
TweetEval: Unified benchmark and comparative evaluation for tweet classification
Francesco Barbieri, Jose Camacho-Collados, Luis Espinosa Anke, and Leonardo Neves. 2020 · 2020
Later among the works it cites.
Back to the future – temporal adaptation of text representations
Johannes Bjerva, Wouter Kouw, and Isabelle Augenstein. 2020 · 2020
Later among the works it cites.
Description based text classification with reinforcement learning
Duo Chai, Wei Wu, Qinghong Han, Fei Wu, and Jiwei Li. 2020 · 2020
Later among the works it cites.
Taming pretrained transformers for extreme multi-label text classification
Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong, Yiming Yang, and Inderjit S. Dhillon. 2020 · 2020
Later among the works it cites.
STANDER: An expert-annotated dataset for news stance detection and evidence retrieval
Costanza Conforti, Jakob Berndt, Mohammad Taher Pilehvar, Chryssi Giannitsarou, Flavio Toxvaerd, and Nigel Collier. 2020a · 2020
Later among the works it cites.
Unsupervised user stance detection on twitter
Kareem Darwish, Peter Stefanov, Michaël Aupetit, and Preslav Nakov. 2020 · 2020
Later among the works it cites.
Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith. 2020 · 2020
Later among the works it cites.
COVIDLies: Detecting COVID-19 misinformation on social media
Tamanna Hossain, Robert L. Logan IV, Arjuna Ugarte, Yoshitomo Matsubara, Sean Young, and Sameer Singh. 2020 · 2020
Later among the works it cites.
Stance detection: A survey
Dilek Küçük and Fazli Can. 2020 · 2020
Later among the works it cites.
Does BERT need domain adaptation for clinical negation detection?
Chen Lin, Steven Bethard, Dmitriy Dligach, Farig Sadeque, Guergana Savova, and Timothy A Miller. 2020 · 2020
Later among the works it cites.
Adapt or get left behind: Domain adaptation through BERT language model finetuning for aspect-target sentiment classification
Alexander Rietzler, Sebastian Stabinger, Paul Opitz, and Stefan Engl. 2020 · 2020
Later among the works it cites.
Predicting the topical stance and political leaning of media using tweets
Peter Stefanov, Kareem Darwish, Atanas Atanasov, and Preslav Nakov. 2020 · 2020
Later among the works it cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Later among the works it cites.
Transformer based multi-source domain adaptation
Dustin Wright and Isabelle Augenstein. 2020 · 2020
Later among the works it cites.
Stance detection in COVID-19 tweets
Kyle Glandt, Sarthak Khanal, Yingjie Li, Doina Caragea, and Cornelia Caragea. 2021 · 2021
Closest in time.
Stance detection benchmark: How robust is your stance detection?
Benjamin Schiller, Johannes Daxenberger, and Iryna Gurevych. 2021 · 2021
Closest in time.
Disembodied machine learning: On the illusion of objectivity in NLP
Zeerak Waseem, Smarika Lulz, Joachim Bingel, and Isabelle Augenstein. 2021 · 2021
Closest in time.
Neural adaptation layers for cross-domain named entity recognition
Bill Yuchen Lin and Wei Lu. 2018 · 2022
Closest in time.
Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky. 2016 · 2030
Closest in time.