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The goal of stance detection is to determine the viewpoint expressed in a piece of text towards a target.
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Liu, Y.; Ott, M.; Goyal, N.; Du, J.; Joshi, M.; Chen, D.; Levy, O.; Lewis, M.; Zettlemoyer, L.; and Stoyanov, V. 2019 · 1907
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WordNet: An electronic lexical database
Miller, G. A. 1998 · 1998
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Language models are few-shot learners
Brown, T. B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al. 2020 · 2005
Earlier work this paper cites.
Detecting Arguing and Sentiment in Meetings
Somasundaran, S.; Ruppenhofer, J.; and Wiebe, J. 2007 · 2007
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Recognizing Stances in Ideological On-Line Debates
Somasundaran, S.; and Wiebe, J. 2010 · 2010
Earlier work this paper cites.
Domain Adaptation via Pseudo In-Domain Data Selection
Axelrod, A.; He, X.; and Gao, J. 2011 · 2011
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Scikit-learn: Machine Learning in Python
Pedregosa, F.; Varoquaux, G.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M.; Prettenhofer, P.; Weiss, R.; Dubourg, V.; Vanderplas, J.; Passos, A.; Cournapeau, D.; Brucher, M.; Perrot, M.; and Édouard Duchesnay. 2011 · 2011
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Efficient Estimation of Word Representations in Vector Space
Mikolov, T.; Chen, K.; Corrado, G.; and Dean, J. 2013 · 2013
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GloVe: Global Vectors for Word Representation
Pennington, J.; Socher, R.; and Manning, C. 2014 · 2014
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A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets
Ebrahimi, J.; Dou, D.; and Lowd, D. 2016 · 2016
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SemEval-2016 Task 6: Detecting Stance in Tweets
Mohammad, S.; Kiritchenko, S.; Sobhani, P.; Zhu, X.; and Cherry, C. 2016 · 2016
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Detecting Stance in Tweets And Analyzing its Interaction with Sentiment
Sobhani, P.; Mohammad, S.; and Kiritchenko, S. 2016 · 2016
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Overview of NLPCC Shared Task 4: Stance Detection in Chinese Microblogs
Xu, R.; Zhou, Y.; Wu, D.; Gui, L.; Du, J.; and Xue, Y. 2016 · 2016
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SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours
Derczynski, L.; Bontcheva, K.; Liakata, M.; Procter, R.; Wong Sak Hoi, G.; and Zubiaga, A. 2017 · 2017
Earlier work this paper cites.
Detecting Stance in Czech News Commentaries
Hercig, T.; Krejzl, P.; Hourová, B.; Steinberger, J.; and Lenc, L. 2017 · 2017
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Bag of Tricks for Efficient Text Classification
Joulin, A.; Grave, E.; Bojanowski, P.; and Mikolov, T. 2017 · 2017
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Fake News Challenge Stage 1 (FNC-I): Stance Detection
Pomerleau, D.; and Rao, D. 2017 · 2017
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Learning to select data for transfer learning with Bayesian Optimization
Ruder, S.; and Plank, B. 2017 · 2017
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Overview of the task on stance and gender detection in tweets on Catalan independence at IberEval 2017
Taulé, M.; Martí, M. A.; Rangel, F. M.; Rosso, P.; Bosco, C.; Patti, V.; et al. 2017 · 2017
Earlier work this paper cites.
Integrating Stance Detection and Fact Checking in a Unified Corpus
Baly, R.; Mohtarami, M.; Glass, J.; Màrquez, L.; Moschitti, A.; and Nakov, P. 2018 · 2018
Earlier work this paper cites.
Stance and sentiment in Czech
Hercig, T.; Krejzl, P.; and Král, P. 2018 · 2018
Earlier work this paper cites.
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
Kudo, T.; and Richardson, J. 2018 · 2018
Earlier work this paper cites.
Stance Evolution and Twitter Interactions in an Italian Political Debate
Lai, M.; Patti, V.; Ruffo, G.; and Rosso, P. 2018 · 2018
Cited alongside, same era.
Stance Detection with Hierarchical Attention Network
Sun, Q.; Wang, Z.; Zhu, Q.; and Zhou, G. 2018 · 2018
Cited alongside, same era.
An English-Hindi Code-Mixed Corpus: Stance Annotation and Baseline System
Swami, S.; Khandelwal, A.; Singh, V.; Akhtar, S.; and Shrivastava, M. 2018 · 2018
Cited alongside, same era.
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Wang, A.; Singh, A.; Michael, J.; Hill, F.; Levy, O.; and Bowman, S. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
Cited alongside, same era.
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Shin, T.; Razeghi, Y.; Logan IV, R. L.; Wallace, E.; and Singh, S. 2020 · 2020
Later among the works it cites.
X-Stance: A Multilingual Multi-Target Dataset for Stance Detection
Vamvas, J.; and Sennrich, R. 2020 · 2020
Later among the works it cites.
Transformers: State-of-the-Art Natural Language Processing
Wolf, T.; Debut, L.; Sanh, V.; Chaumond, J.; Delangue, C.; Moi, A.; Cistac, P.; Rault, T.; Louf, R.; Funtowicz, M.; Davison, J.; Shleifer, S.; von Platen, P.; Ma, C.; Jernite, Y.; Plu, J.; Xu, C.; Le Scao, T.; Gugger, S.; Drame, M.; Lhoest, Q.; and Rush, A. 2020 · 2020
Later among the works it cites.
VaxxStance: Going Beyond Text in Cross-lingual Stance Detection
Agerri, R.; Centeno, R.; Espnosa, M.; Fernandez de Landa, J.; and Rodrigo, A. 2021 · 2021
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AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking
Alhindi, T.; Alabdulkarim, A.; Alshehri, A.; Abdul-Mageed, M.; and Nakov, P. 2021 · 2021
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Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling
Han, X.; and Eisenstein, J. 2019 · 2019
Cited alongside, same era.
Multi-Task Stance Detection with Sentiment and Stance Lexicons
Li, Y.; and Caragea, C. 2019 · 2019
Cited alongside, same era.
Joint Rumour Stance and Veracity Prediction
Lillie, A. E.; Middelboe, E. R.; and Derczynski, L. 2019 · 2019
Cited alongside, same era.
Decoupled Weight Decay Regularization
Loshchilov, I.; and Hutter, F. 2019 · 2019
Cited alongside, same era.
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Paszke, A.; Gross, S.; Massa, F.; Lerer, A.; Bradbury, J.; Chanan, G.; Killeen, T.; Lin, Z.; Gimelshein, N.; Antiga, L.; Desmaison, A.; Kopf, A.; Yang, E.; DeVito, Z.; Raison, M.; Tejani, A.; Chilamkurthy, S.; Steiner, B.; Fang, L.; Bai, J.; and Chintala, S. 2019 · 2019
Cited alongside, same era.
Language Models as Knowledge Bases?
Petroni, F.; Rocktäschel, T.; Riedel, S.; Lewis, P.; Bakhtin, A.; Wu, Y.; and Miller, A. 2019 · 2019
Cited alongside, same era.
Stance detection via sentiment information and neural network model
Sun, Q.; Wang, Z.; Li, S.; Zhu, Q.; and Zhou, G. 2019 · 2019
Cited alongside, same era.
Barbieri, F.; Anke, L. E.; and Camacho-Collados, J. 2021 · 2021
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On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
Bender, E. M.; Gebru, T.; McMillan-Major, A.; and Shmitchell, S. 2021 · 2021
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Making Pre-trained Language Models Better Few-shot Learners
Gao, T.; Fisch, A.; and Chen, D. 2021 · 2021
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Cross-Domain Label-Adaptive Stance Detection
Hardalov, M.; Arora, A.; Nakov, P.; and Augenstein, I. 2021 · 2021
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How many data points is a prompt worth?
Le Scao, T.; and Rush, A. 2021 · 2021
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The Power of Scale for Parameter-Efficient Prompt Tuning
Lester, B.; Al-Rfou, R.; and Constant, N. 2021 · 2021
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Prefix-Tuning: Optimizing Continuous Prompts for Generation
Li, X. L.; and Liang, P. 2021 · 2021
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Liu, P.; Yuan, W.; Fu, J.; Jiang, Z.; Hayashi, H.; and Neubig, G. 2021 · 2021
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Cutting down on prompts and parameters: Simple few-shot learning with language models
Logan IV, R. L.; Balažević, I.; Wallace, E.; Petroni, F.; Singh, S.; and Riedel, S. 2021 · 2021
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On the Stability of Fine-tuning {BERT}: Misconceptions, Explanations, and Strong Baselines
Mosbach, M.; Andriushchenko, M.; and Klakow, D. 2021 · 2021
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What to Pre-Train on? Efficient Intermediate Task Selection
Poth, C.; Pfeiffer, J.; Rücklé, A.; and Gurevych, I. 2021 · 2021
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Learning How to Ask: Querying LMs with Mixtures of Soft Prompts
Qin, G.; and Eisner, J. 2021 · 2021
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Stance detection benchmark: How robust is your stance detection?
Schiller, B.; Daxenberger, J.; and Gurevych, I. 2021 · 2021
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A Stance Detection Approach Based on Generalized Autoregressive Pretrained Language Model in Chinese Microblogs
Su, Z.; Xi, Y.; Cao, R.; Tang, H.; and Pan, H. 2021 · 2021
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Improving and simplifying pattern exploiting training
Tam, D.; Menon, R. R.; Bansal, M.; Srivastava, S.; and Raffel, C. 2021 · 2021
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Disembodied machine learning: On the illusion of objectivity in NLP
Waseem, Z.; Lulz, S.; Bingel, J.; and Augenstein, I. 2021 · 2021
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