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Neural Check-Worthiness Ranking with Weak Supervision: Finding Sentences for Fact-Checking.

, , , , and . WWW (Companion Volume), page 994-1000. ACM, (2019)

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Neural Check-Worthiness Ranking with Weak Supervision: Finding Sentences for Fact-Checking., , , , and . WWW (Companion Volume), page 994-1000. ACM, (2019)Detecting Faults during Automatic Screwdriving: A Dataset and Use Case of Anomaly Detection for Automatic Screwdriving., , , and . CoRR, (2021)Predicting distresses using deep learning of text segments in annual reports., , , and . Expert Syst. Appl., (2019)Contextual and Sequential User Embeddings for Large-Scale Music Recommendation., , , , , , and . RecSys, page 53-62. ACM, (2020)MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims., , , , , , and . EMNLP/IJCNLP (1), page 4684-4696. Association for Computational Linguistics, (2019)Unsupervised Multi-Index Semantic Hashing., , , , and . WWW, page 2879-2889. ACM / IW3C2, (2021)DeepTimeAnomalyViz: A Tool for Visualizing and Post-processing Deep Learning Anomaly Detection Results for Industrial Time-Series., , and . CoRR, (2021)Unsupervised Semantic Hashing with Pairwise Reconstruction., , , , and . SIGIR, page 2009-2012. ACM, (2020)Modelling Sequential Music Track Skips using a Multi-RNN Approach., , , , and . CoRR, (2019)Neural Weakly Supervised Fact Check-Worthiness Detection with Contrastive Sampling-Based Ranking Loss., , , and . CLEF (Working Notes), volume 2380 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)