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Publication search results
found 34 matches
- 2021
- Alham Fikri Aji, Made Nindyatama Nityasya, Haryo Akbarianto Wibowo, Radityo Eko Prasojo, Tirana Fatyanosa:
BERT Goes Brrr: A Venture Towards the Lesser Error in Classifying Medical Self-Reporters on Twitter. SMM4H@NAACL-HLT 2021: 58-64 - Pavel Blinov:
Text Augmentation Techniques in Drug Adverse Effect Detection Task. SMM4H@NAACL-HLT 2021: 95-97 - Sergio Santamaria Carrasco, Roberto Cuervo Rosillo:
Word Embeddings, Cosine Similarity and Deep Learning for Identification of Professions & Occupations in Health-related Social Media. SMM4H@NAACL-HLT 2021: 74-76 - Joseph Cornelius, Tilia Ellendorff, Fabio Rinaldi:
Approaching SMM4H with auto-regressive language models and back-translation. SMM4H@NAACL-HLT 2021: 146-148 - George-Andrei Dima, Dumitru-Clementin Cercel, Mihai Dascalu:
Transformer-based Multi-Task Learning for Adverse Effect Mention Analysis in Tweets. SMM4H@NAACL-HLT 2021: 44-51 - Mohab Elkaref, Lamiece Hassan:
A Joint Training Approach to Tweet Classification and Adverse Effect Extraction and Normalization for SMM4H 2021. SMM4H@NAACL-HLT 2021: 91-94 - David Carreto Fidalgo, Daniel Vila-Suero, Francisco Aranda Montes, Ignacio Talavera:
System description for ProfNER - SMMH: Optimized finetuning of a pretrained transformer and word vectors. SMM4H@NAACL-HLT 2021: 69-73 - Max Fleming, Priyanka Dondeti, Caitlin N. Dreisbach, Adam Poliak:
Fine-tuning Transformers for Identifying Self-Reporting Potential Cases and Symptoms of COVID-19 in Tweets. SMM4H@NAACL-HLT 2021: 131-134 - Yuting Guo, Yao Ge, Mohammed Ali Al-Garadi, Abeed Sarker:
Pre-trained Transformer-based Classification and Span Detection Models for Social Media Health Applications. SMM4H@NAACL-HLT 2021: 52-57 - Zongcheng Ji, Tian Xia, Mei Han:
PAII-NLP at SMM4H 2021: Joint Extraction and Normalization of Adverse Drug Effect Mentions in Tweets. SMM4H@NAACL-HLT 2021: 126-127 - Payam Karisani, Jinho D. Choi, Li Xiong:
View Distillation with Unlabeled Data for Extracting Adverse Drug Effects from User-Generated Data. SMM4H@NAACL-HLT 2021: 7-12 - Tanay Kayastha, Pranjal Gupta, Pushpak Bhattacharyya:
BERT based Adverse Drug Effect Tweet Classification. SMM4H@NAACL-HLT 2021: 88-90 - Deepak Kumar, Nalin Kumar, Subhankar Mishra:
NLP@NISER: Classification of COVID19 tweets containing symptoms. SMM4H@NAACL-HLT 2021: 102-104 - Adarsh Kumar, Ojasv Kamal, Susmita Mazumdar:
Adversities are all you need: Classification of self-reported breast cancer posts on Twitter using Adversarial Fine-tuning. SMM4H@NAACL-HLT 2021: 112-114 - Lung-Hao Lee, Man-Chen Hung, Chien-Huan Lu, Chang-Hao Chen, Po-Lei Lee, Kuo-Kai Shyu:
Classification of Tweets Self-reporting Adverse Pregnancy Outcomes and Potential COVID-19 Cases Using RoBERTa Transformers. SMM4H@NAACL-HLT 2021: 98-101 - Frances Adriana Laureano De Leon, Harish Tayyar Madabushi, Mark Lee:
UoB at ProfNER 2021: Data Augmentation for Classification Using Machine Translation. SMM4H@NAACL-HLT 2021: 115-117 - Ying Luo, Lis Pereira, Ichiro Kobayashi:
OCHADAI at SMM4H-2021 Task 5: Classifying self-reporting tweets on potential cases of COVID-19 by ensembling pre-trained language models. SMM4H@NAACL-HLT 2021: 123-125 - Arjun Magge, Ari Z. Klein, Antonio Miranda-Escalada, Mohammed Ali Al-Garadi, Ilseyar Alimova, Zulfat Miftahutdinov, Eulàlia Farré, Salvador Lima-López, Ivan Flores, Karen O'Connor, Davy Weissenbacher, Elena Tutubalina, Abeed Sarker, Juan M. Banda, Martin Krallinger, Graciela Gonzalez-Hernandez:
Overview of the Sixth Social Media Mining for Health Applications (#SMM4H) Shared Tasks at NAACL 2021. SMM4H@NAACL-HLT 2021: 21-32 - José-Alberto Mesa-Murgado, Ana Belén Parras Portillo, Pilar López-Úbeda, María Teresa Martín-Valdivia, Luis Alfonso Ureña López:
Identifying professions & occupations in Health-related Social Media using Natural Language Processing. SMM4H@NAACL-HLT 2021: 141-145 - Antonio Miranda-Escalada, Eulàlia Farré-Maduell, Salvador Lima-López, Luis Gascó, Vicent Brivá-Iglesias, Marvin Agüero-Torales, Martin Krallinger:
The ProfNER shared task on automatic recognition of occupation mentions in social media: systems, evaluation, guidelines, embeddings and corpora. SMM4H@NAACL-HLT 2021: 13-20 - Anupam Mondal, Sainik Kumar Mahata, Monalisa Dey, Dipankar Das:
Classification of COVID19 tweets using Machine Learning Approaches. SMM4H@NAACL-HLT 2021: 135-137 - Jingcheng Niu, Erin E. Rees, Victoria Ng, Gerald Penn:
Statistically Evaluating Social Media Sentiment Trends towards COVID-19 Non-Pharmaceutical Interventions with Event Studies. SMM4H@NAACL-HLT 2021: 1-6 - Atul Kr. Ojha, Priya Rani, Koustava Goswami, Bharathi Raja Chakravarthi, John P. McCrae:
ULD-NUIG at Social Media Mining for Health Applications (#SMM4H) Shared Task 2021. SMM4H@NAACL-HLT 2021: 149-152 - Victoria Pachón, Jacinto Mata Vázquez, Juan Luis Domínguez-Olmedo:
Identification of profession & occupation in Health-related Social Media using tweets in Spanish. SMM4H@NAACL-HLT 2021: 105-107 - Vasile Pais, Maria Mitrofan:
Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media. SMM4H@NAACL-HLT 2021: 128-130 - Varad Pimpalkhute, Prajwal Nakhate, Tausif Diwan:
IIITN NLP at SMM4H 2021 Tasks: Transformer Models for Classification on Health-Related Imbalanced Twitter Datasets. SMM4H@NAACL-HLT 2021: 118-122 - Sidharth R, Abhiraj Tiwari, Parthivi Choubey, Saisha Kashyap, Sahil Khose, Kumud Lakara, Nishesh Singh, Ujjwal Verma:
BERT based Transformers lead the way in Extraction of Health Information from Social Media. SMM4H@NAACL-HLT 2021: 33-38 - Rajarshi Roychoudhury, Sudip Kumar Naskar:
Fine-tuning BERT to classify COVID19 tweets containing symptoms. SMM4H@NAACL-HLT 2021: 138-140 - Pedro Ruas, Vitor D. T. Andrade, Francisco M. Couto:
Lasige-BioTM at ProfNER: BiLSTM-CRF and contextual Spanish embeddings for Named Entity Recognition and Tweet Binary Classification. SMM4H@NAACL-HLT 2021: 108-111 - Andrey Sakhovskiy, Zulfat Miftahutdinov, Elena Tutubalina:
KFU NLP Team at SMM4H 2021 Tasks: Cross-lingual and Cross-modal BERT-based Models for Adverse Drug Effects. SMM4H@NAACL-HLT 2021: 39-43
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