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Paraphrase Identification

18 papers with code · Natural Language Processing

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Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning

ICLR 2018 facebookresearch/InferSent

In this work, we present a simple, effective multi-task learning framework for sentence representations that combines the inductive biases of diverse training objectives in a single model.

MULTI-TASK LEARNING NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION SEMANTIC TEXTUAL SIMILARITY

Multi-Task Deep Neural Networks for Natural Language Understanding

31 Jan 2019namisan/mt-dnn

In this paper, we present a Multi-Task Deep Neural Network (MT-DNN) for learning representations across multiple natural language understanding (NLU) tasks.

DOMAIN ADAPTATION LANGUAGE MODELLING NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION SENTIMENT ANALYSIS

Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question Answering

COLING 2018 lanwuwei/SPM_toolkit

In this paper, we analyze several neural network designs (and their variations) for sentence pair modeling and compare their performance extensively across eight datasets, including paraphrase identification, semantic textual similarity, natural language inference, and question answering tasks.

NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION QUESTION ANSWERING SEMANTIC TEXTUAL SIMILARITY SENTENCE PAIR MODELING

Character-based Neural Networks for Sentence Pair Modeling

HLT 2018 lanwuwei/SPM_toolkit

Sentence pair modeling is critical for many NLP tasks, such as paraphrase identification, semantic textual similarity, and natural language inference.

NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION SEMANTIC TEXTUAL SIMILARITY SENTENCE PAIR MODELING

Natural Language Inference over Interaction Space

ICLR 2018 YichenGong/Densely-Interactive-Inference-Network

Natural Language Inference (NLI) task requires an agent to determine the logical relationship between a natural language premise and a natural language hypothesis.

NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION

Sentence Similarity Learning by Lexical Decomposition and Composition

COLING 2016 Leputa/CIKM-AnalytiCup-2018

Most conventional sentence similarity methods only focus on similar parts of two input sentences, and simply ignore the dissimilar parts, which usually give us some clues and semantic meanings about the sentences.

PARAPHRASE IDENTIFICATION QUESTION ANSWERING

ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs

TACL 2016 Leputa/CIKM-AnalytiCup-2018

(ii) We propose three attention schemes that integrate mutual influence between sentences into CNN; thus, the representation of each sentence takes into consideration its counterpart.

ANSWER SELECTION NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION

A Deep Relevance Matching Model for Ad-hoc Retrieval

23 Nov 2017faneshion/DRMM

Specifically, our model employs a joint deep architecture at the query term level for relevance matching.

AD-HOC INFORMATION RETRIEVAL PARAPHRASE IDENTIFICATION QUESTION ANSWERING SPEECH RECOGNITION

Modelling Sentence Pairs with Tree-structured Attentive Encoder

COLING 2016 yoosan/sentpair

We describe an attentive encoder that combines tree-structured recursive neural networks and sequential recurrent neural networks for modelling sentence pairs.

PARAPHRASE IDENTIFICATION SEMANTIC TEXTUAL SIMILARITY