Papers
Teaching Machines to Extract Main Content for Machine Reading Comprehension
Zhaohui Li, Yue Feng, Jun Xu et al.
Teaching Multiple Concepts to a Forgetful Learner
Anette Hunziker, Yuxin Chen, Oisin Mac Aodha et al.
Team Bertha von Suttner at SemEval-2019 Task 4: Hyperpartisan News Detection using ELMo Sentence Representation Convolutional Network
Ye Jiang, Johann Petrak, Xingyi Song et al.
Team DOMLIN: Exploiting Evidence Enhancement for the FEVER Shared Task
Dominik Stammbach, Guenter Neumann
Team Fernando-Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection
André Cruz, Gil Rocha, Rui Sousa-Silva et al.
Team GPLSI. Approach for automated fact checking
Aimée Alonso-Reina, Robiert Sepúlveda-Torres, Estela Saquete et al.
Team Harry Friberg at SemEval-2019 Task 4: Identifying Hyperpartisan News through Editorially Defined Metatopics
Nazanin Afsarmanesh, Jussi Karlgren, Peter Sumbler et al.
Team Howard Beale at SemEval-2019 Task 4: Hyperpartisan News Detection with BERT
Osman Mutlu, Ozan Arkan Can, Erenay Dayanik
Team Jack Ryder at SemEval-2019 Task 4: Using BERT Representations for Detecting Hyperpartisan News
Daniel Shaprin, Giovanni Da San Martino, Alberto Barrón-Cedeño et al.
Team JUST at the MADAR Shared Task on Arabic Fine-Grained Dialect Identification
Bashar Talafha, Ali Fadel, Mahmoud Al-Ayyoub et al.
Team Kermit-the-frog at SemEval-2019 Task 4: Bias Detection Through Sentiment Analysis and Simple Linguistic Features
Talita Anthonio, Lennart Kloppenburg
Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System
Rebekah Cramerus, Tatjana Scheffler
Team Ned Leeds at SemEval-2019 Task 4: Exploring Language Indicators of Hyperpartisan Reporting
Bozhidar Stevanoski, Sonja Gievska
Team Peter Brinkmann at SemEval-2019 Task 4: Detecting Biased News Articles Using Convolutional Neural Networks
Michael Färber, Agon Qurdina, Lule Ahmedi
Team Peter-Parker at SemEval-2019 Task 4: BERT-Based Method in Hyperpartisan News Detection
Zhiyuan Ning, Yuanzhen Lin, Ruichao Zhong
Team QCRI-MIT at SemEval-2019 Task 4: Propaganda Analysis Meets Hyperpartisan News Detection
Abdelrhman Saleh, Ramy Baly, Alberto Barrón-Cedeño et al.
Team SVMrank: Leveraging Feature-rich Support Vector Machines for Ranking Explanations to Elementary Science Questions
Jennifer D’Souza, Isaiah Onando Mulang’, Sören Auer
Team Taurus at SemEval-2019 Task 9: Expert-informed pattern recognition for suggestion mining
Nelleke Oostdijk, Hans van Halteren
Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks
Albin Zehe, Lena Hettinger, Stefan Ernst et al.
Team yeon-zi at SemEval-2019 Task 4: Hyperpartisan News Detection by De-noising Weakly-labeled Data
Nayeon Lee, Zihan Liu, Pascale Fung
TEASPN: Framework and Protocol for Integrated Writing Assistance Environments
Masato Hagiwara, Takumi Ito, Tatsuki Kuribayashi et al.
TEASPN: Framework and Protocol for Integrated Writing Assistance Environments
Masato Hagiwara, Takumi Ito, Tatsuki Kuribayashi et al.
Technical, Hard and Explainable Question Answering (THE-QA)
Shailaja Sampat
TECHSSN at SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Tweets using Deep Neural Networks
Logesh Balasubramanian, Harshini Sathish Kumar, Geetika Bandlamudi et al.