Aicyber at SemEval-2016 Task 4: i-vector based sentence representation
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Aicyber's System for NLPCC 2017 Shared Task 2: Voting of Baselines
This paper presents Aicyber's system for NLPCC 2017 shared task 2. It is formed by a voting of three deep learning based system trained on character-enhanced word vectors and a well known bag-of-word model.
Deep LearningTask 2LIM-LIG at SemEval-2017 Task1: Enhancing the Semantic Similarity for Arabic Sentences with Vectors Weighting
This article describes our proposed system named LIM-LIG. This system is designed for SemEval 2017 Task1: Semantic Textual Similarity (Track1). LIM-LIG proposes an innovative enhancement to word embedding-based model dev…
DescriptiveInformation RetrievalMachine TranslationParaphrase Identification+6Representing Sentences as Low-Rank Subspaces
Sentences are important semantic units of natural language. A generic, distributional representation of sentences that can capture the latent semantics is beneficial to multiple downstream applications. We observe a simp…
Semantic Textual SimilaritySentenceTakeLab at SemEval-2018 Task12: Argument Reasoning Comprehension with Skip-Thought Vectors
This paper describes our system for the SemEval-2018 Task 12: Argument Reasoning Comprehension Task. We utilize skip-thought vectors, sentence-level distributional vectors inspired by the popular word embeddings and the …
Common Sense ReasoningNatural Language InferenceSentenceWord EmbeddingsPlusEmo2Vec at SemEval-2018 Task 1: Exploiting emotion knowledge from emoji and #hashtags
This paper describes our system that has been submitted to SemEval-2018 Task 1: Affect in Tweets (AIT) to solve five subtasks. We focus on modeling both sentence and word level representations of emotion inside texts thr…
BIG-bench Machine LearningregressionSentence