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User-generated texts available on the web and social platforms are often long and semantically challenging, making them difficult to annotate.
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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Towards realistic practices in low-resource natural language processing: The development set
Kann, K.; Cho, K.; and Bowman, S. R. 2019 · 1909
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Data Augmentation for Radiology Report Simplification
Yang, Z.; Cherian, S.; and Vucetic, S. 2023 · 1932
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A new readability yardstick
Flesch, R. 1948 · 1948
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MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers
Wang, W.; Wei, F.; Dong, L.; Bao, H.; Yang, N.; and Zhou, M. 2020 · 2002
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CoAID: COVID-19 Healthcare Misinformation Dataset
Cui, L.; and Lee, D. 2020 · 2006
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Low-resource Languages: A Review of Past Work and Future Challenges
Magueresse, A.; Carles, V.; and Heetderks, E. 2020 · 2006
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Dependency distance as a metric of language comprehension difficulty
Liu, H. 2008 · 2008
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Abstract meaning representation for sembanking
Banarescu, L.; Bonial, C.; Cai, S.; Georgescu, M.; Griffitt, K.; Hermjakob, U.; Knight, K.; Koehn, P.; Palmer, M.; and Schneider, N. 2013 · 2013
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Smatch: an Evaluation Metric for Semantic Feature Structures
Cai, S.; and Knight, K. 2013 · 2013
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A large annotated corpus for learning natural language inference
Bowman, S. R.; Angeli, G.; Potts, C.; and Manning, C. D. 2015 · 2015
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SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation
Cer, D.; Diab, M.; Agirre, E.; Lopez-Gazpio, I.; and Specia, L. 2017 · 2017
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Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts
Cocos, A.; Fiks, A. G.; and Masino, A. J. 2017 · 2017
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Efficient Natural Language Response Suggestion for Smart Reply
Henderson, M. L.; Al-Rfou, R.; Strope, B.; Sung, Y.; Lukács, L.; Guo, R.; Kumar, S.; Miklos, B.; and Kurzweil, R. 2017 · 2017
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Preclude: Conflict detection in textual health advice
Preum, S. M.; Mondol, A. S.; Ma, M.; Wang, H.; and Stankovic, J. A. 2017 · 2017
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BIOSSES: a semantic sentence similarity estimation system for the biomedical domain
Soğancıoğlu, G.; Öztürk, H.; and Özgür, A. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2018 · 2018
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Identifying Emotional Support in Online Health Communities
Khanpour, H.; Caragea, C.; and Biyani, P. 2018 · 2018
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AMR Beyond the Sentence: the Multi-sentence AMR corpus
O’Gorman, T.; Regan, M.; Griffitt, K.; Hermjakob, U.; Knight, K.; and Palmer, M. 2018 · 2018
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A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Williams, A.; Nangia, N.; and Bowman, S. 2018 · 2018
Cited alongside, same era.
Publicly Available Clinical BERT Embeddings
Alsentzer, E.; Murphy, J.; Boag, W.; Weng, W.-H.; Jindi, D.; Naumann, T.; and McDermott, M. 2019 · 2019
Cited alongside, same era.
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Reimers, N.; and Gurevych, I. 2019 · 2019
Cited alongside, same era.
CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts
Zirikly, A.; Resnik, P.; Uzuner, Ö.; and Hollingshead, K. 2019 · 2019
SimCSE: Simple Contrastive Learning of Sentence Embeddings
Gao, T.; Yao, X.; and Chen, D. 2021 · 2021
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A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios
Hedderich, M. A.; Lange, L.; Adel, H.; Strötgen, J.; and Klakow, D. 2021 · 2021
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Knowledge Enhanced Masked Language Model for Stance Detection
Kawintiranon, K.; and Singh, L. 2021 · 2021
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Detecting Health Advice in Medical Research Literature
Li, Y.; Wang, J.; and Yu, B. 2021 · 2021
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Explainable unsupervised argument similarity rating with Abstract Meaning Representation and conclusion generation
Opitz, J.; Heinisch, P.; Wiesenbach, P.; Cimiano, P.; and Frank, A. 2021 · 2021
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Semantic-based Pre-training for Dialogue Understanding
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Cited alongside, same era.
Dialogue-AMR: abstract meaning representation for dialogue
Bonial, C.; Donatelli, L.; Abrams, M.; Lukin, S.; Tratz, S.; Marge, M.; Artstein, R.; Traum, D.; and Voss, C. 2020 · 2020
Cited alongside, same era.
Coronavirus goes viral: quantifying the COVID-19 misinformation epidemic on Twitter
Kouzy, R.; Abi Jaoude, J.; Kraitem, A.; El Alam, M. B.; Karam, B.; Adib, E.; Zarka, J.; Traboulsi, C.; Akl, E. W.; and Baddour, K. 2020 · 2020
Cited alongside, same era.
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
Lewis, M.; Liu, Y.; Goyal, N.; Ghazvininejad, M.; Mohamed, A.; Levy, O.; Stoyanov, V.; and Zettlemoyer, L. 2020 · 2020
Cited alongside, same era.
How Effective is Task-Agnostic Data Augmentation for Pre-trained Transformers?
Longpre, S.; Wang, Y.; and DuBois, C. 2020 · 2020
Cited alongside, same era.
GPT-too: A Language-Model-First Approach for AMR-to-Text Generation
Mager, M.; Fernandez Astudillo, R.; Naseem, T.; Sultan, M. A.; Lee, Y.-S.; Florian, R.; and Roukos, S. 2020 · 2020
Cited alongside, same era.
Effective Transfer Learning for Identifying Similar Questions: Matching User Questions to COVID-19 FAQs
McCreery, C. H.; Katariya, N.; Kannan, A.; Chablani, M.; and Amatriain, X. 2020 · 2020
Cited alongside, same era.
Bai, X.; Song, L.; and Zhang, Y. 2022 · 2022
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Retrofitting Multilingual Sentence Embeddings with Abstract Meaning Representation
Cai, D.; Li, X.; Ho, J. C.-S.; Bing, L.; and Lam, W. 2022 · 2022
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Scope of Pre-trained Language Models for Detecting Conflicting Health Information
Gatto, J.; Basak, M.; and Preum, S. M. 2022 · 2022
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Grover, K.; Angara, S. M. P.; Akhtar, M. S.; and Chakraborty, T. 2022 · 2022
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Cross-Domain Sentiment Classification using Semantic Representation
Li, S.; Wang, Z.; Jiang, X.; and Zhou, G. 2022b · 2022
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Predicate-argument based bi-encoder for paraphrase identification
Peng, Q.; Weir, D.; Weeds, J.; and Chai, Y. 2022 · 2022
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Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource Constraints
Rohanian, O.; Jauncey, H.; Nouriborji, M.; Gonçalves, B. P.; Kartsonaki, C.; Group, I. C. C.; Merson, L.; and Clifton, D. 2022 · 2022
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FaCov: COVID-19 Viral News and Rumors Fact-Check Articles Dataset
Sharma, S.; Agrawal, E.; Sharma, R.; and Datta, A. 2022 · 2022
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AMR-DA: Data Augmentation by Abstract Meaning Representation
Shou, Z.; Jiang, Y.; and Lin, F. 2022 · 2022
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Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims
Srba, I.; Pecher, B.; Tomlein, M.; Moro, R.; Stefancova, E.; Simko, J.; and Bielikova, M. 2022 · 2022
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To Augment or Not to Augment? A Comparative Study on Text Augmentation Techniques for Low-Resource NLP
Şahin, G. G. 2022 · 2022
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