UNBNLP at SemEval-2016 Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation
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Semantic Textual SimilarityWord EmbeddingsSimilar Papers 제목 키워드 기반
FCICU at SemEval-2017 Task 1: Sense-Based Language Independent Semantic Textual Similarity Approach
This paper describes FCICU team systems that participated in SemEval-2017 Semantic Textual Similarity task (Task1) for monolingual and cross-lingual sentence pairs. A sense-based language independent textual similarity a…
Machine TranslationSemantic Textual SimilaritySentenceITNLP-AiKF at SemEval-2017 Task 1: Rich Features Based SVR for Semantic Textual Similarity Computing
Semantic Textual Similarity (STS) devotes to measuring the degree of equivalence in the underlying semantic of the sentence pair. We proposed a new system, ITNLP-AiKF, which applies in the SemEval 2017 Task1 Semantic Tex…
Feature EngineeringregressionSemantic Textual SimilaritySentence+1UNBNLP at SemEval-2021 Task 1: Predicting lexical complexity with masked language models and character-level encoders
In this paper, we present three supervised systems for English lexical complexity prediction of single and multiword expressions for SemEval-2021 Task 1. We explore the use of statistical baseline features, masked langua…
Lexical Complexity PredictionPredictionL2F/INESC-ID at SemEval-2017 Tasks 1 and 2: Lexical and semantic features in word and textual similarity
This paper describes our approach to the SemEval-2017 {``}Semantic Textual Similarity{''} and {``}Multilingual Word Similarity{''} tasks. In the former, we test our approach in both English and Spanish, and use a linguis…
Abstract Meaning RepresentationSemantic Textual SimilarityWord EmbeddingsWord SimilarityBL.Research at SemEval-2022 Task 8: Using various Semantic Information to evaluate document-level Semantic Textual Similarity
This paper presents our system for document-level semantic textual similarity (STS) evaluation at SemEval-2022 Task 8: “Multilingual News Article Similarity”. The semantic information used is obtained by using different …
Document ClassificationSemantic Textual SimilaritySTS