Papers with word selection

3 papers
Analysing Coreference in Transformer Outputs (D19-65)

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Challenge: Using a transformer architecture, we study coreference phenomena in three neural machine translation systems.
Approach: They analyse coreference phenomena in three neural machine translation systems . they manually annotate (the possibly incorrect) coreference chains in the outputs .
Outcome: The proposed model shows stronger translationese effects in machine translated outputs than in human translations.
Enhancing Air Quality Prediction with Social Media and Natural Language Processing (P19-1)

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Challenge: predicting air quality is a major concern for human health, but the changes of air quality conditions are still difficult to monitor.
Approach: They propose to exploit social media and natural language processing techniques to enhance air quality prediction.
Outcome: The proposed approach improves air quality prediction over baseline that does not use social media by 6.9% to 17.7% in macro-F1 scores.
Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning (D19-1)

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Challenge: Recent neural networks have shown promising results on Document-level Aspect Sentiment Classification (DASC) however, these approaches often offer little transparency w.r.t. their inner working mechanisms and lack interpretability.
Approach: They propose a Hierarchical Reinforcement Learning approach to DASC that incorporates clause selection and word selection strategies to tackle the data noise problem.
Outcome: The proposed approach over the state-of-the-art approaches shows impressive performance over the current baselines.

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