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SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment

Paper Details:

Month: August
Year: 2014
Location: Dublin, Ireland
Venue: *SEMEVAL |
SIG: SIGLEX

Citations

URL

Adopting the Word-Pair-Dependency-Triplets with Individual Comparison for Natural Language Inference
Qianlong Du | Chengqing Zong | Keh-Yih Su |

Convolutional Neural Network for Universal Sentence Embeddings
Xiaoqi Jiao | Fang Wang | Dan Feng |

A large annotated corpus for learning natural language inference
Samuel R. Bowman | Gabor Angeli | Christopher Potts | Christopher D. Manning |

Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks
Hua He | Kevin Gimpel | Jimmy Lin |

Charagram: Embedding Words and Sentences via Character n-grams
John Wieting | Mohit Bansal | Kevin Gimpel | Karen Livescu |

Learning Paraphrastic Sentence Embeddings from Back-Translated Bitext
John Wieting | Jonathan Mallinson | Kevin Gimpel |

A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks
Kazuma Hashimoto | Caiming Xiong | Yoshimasa Tsuruoka | Richard Socher |

Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement
Hua He | Jimmy Lin |

A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Adina Williams | Nikita Nangia | Samuel Bowman |

Lexical Substitution for Evaluating Compositional Distributional Models
Maja Buljan | Sebastian Padó | Jan Šnajder |

Jointly optimizing word representations for lexical and sentential tasks with the C-PHRASE model
Nghia The Pham | Germán Kruszewski | Angeliki Lazaridou | Marco Baroni |

Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
Kai Sheng Tai | Richard Socher | Christopher D. Manning |

Polish evaluation dataset for compositional distributional semantics models
Alina Wróblewska | Katarzyna Krasnowska-Kieraś |

Revisiting Recurrent Networks for Paraphrastic Sentence Embeddings
John Wieting | Kevin Gimpel |

Deriving Boolean structures from distributional vectors
German Kruszewski | Denis Paperno | Marco Baroni |

Analysis Methods in Neural Language Processing: A Survey
Yonatan Belinkov | James Glass |

SemEval-2014 Task 3: Cross-Level Semantic Similarity
David Jurgens | Mohammad Taher Pilehvar | Roberto Navigli |

FBK-TR: SVM for Semantic Relatedeness and Corpus Patterns for RTE
Ngoc Phuoc An Vo | Octavian Popescu | Tommaso Caselli |

Illinois-LH: A Denotational and Distributional Approach to Semantics
Alice Lai | Julia Hockenmaier |

RTM-DCU: Referential Translation Machines for Semantic Similarity
Ergun Biçici | Andy Way |

SemantiKLUE: Robust Semantic Similarity at Multiple Levels Using Maximum Weight Matching
Thomas Proisl | Stefan Evert | Paul Greiner | Besim Kabashi |

TakeLab at SemEval-2018 Task12: Argument Reasoning Comprehension with Skip-Thought Vectors
Ana Brassard | Tin Kuculo | Filip Boltužić | Jan Šnajder |

Referential Translation Machines for Predicting Translation Quality
Ergun Biçici | Andy Way |

Recursive Neural Networks Can Learn Logical Semantics
Samuel R. Bowman | Christopher Potts | Christopher D. Manning |

SLEDDED: A Proposed Dataset of Event Descriptions for Evaluating Phrase Representations
Laura Rimell | Eva Maria Vecchi |

Field Of Study

Task

Textual Entailment Semantic Similarity

Language

English

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