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ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention

2018-06-01 · SEMEVAL 2018 6 · Wenjie Liu, Chengjie Sun, Lei Lin, Bingquan Liu

Reasoning is a very important topic and has many important applications in the field of natural language processing. Semantic Evaluation (SemEval) 2018 Task 12 {``}The Argument Reasoning Comprehension{''} committed to research natural language reasoning. In this task, we proposed a novel argument reasoning comprehension system, ITNLP-ARC, which use Neural Networks technology to solve this problem. In our system, the LSTM model is involved to encode both the premise sentences and the warrant sentences. The attention model is used to merge the two premise sentence vectors. Through comparing the similarity between the attention vector and each of the two warrant vectors, we choose the one with higher similarity as our system{'}s final answer.

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ARCInformation RetrievalMachine TranslationNatural Language InferenceRelation ExtractionSemantic Textual SimilaritySentenceText Summarization

Methods 이 논문이 사용한 방법론

Sigmoid Activation 설명 없음
Tanh Activation 설명 없음
LSTM An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla…

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