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Semantic Textual Similarity

96 papers with code · Natural Language Processing

Semantic textual similarity deals with determining how similar two pieces of texts are. This can take the form of assigning a score from 1 to 5. Related tasks are paraphrase or duplicate identification.

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Greatest papers with code

XLNet: Generalized Autoregressive Pretraining for Language Understanding

19 Jun 2019huggingface/pytorch-pretrained-BERT

With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling.

DOCUMENT RANKING LANGUAGE MODELLING NATURAL LANGUAGE INFERENCE QUESTION ANSWERING READING COMPREHENSION SEMANTIC TEXTUAL SIMILARITY SENTIMENT ANALYSIS TEXT CLASSIFICATION

ERNIE 2.0: A Continual Pre-training Framework for Language Understanding

29 Jul 2019PaddlePaddle/ERNIE

Recently, pre-trained models have achieved state-of-the-art results in various language understanding tasks, which indicates that pre-training on large-scale corpora may play a crucial role in natural language processing.

LINGUISTIC ACCEPTABILITY MULTI-TASK LEARNING NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC TEXTUAL SIMILARITY SENTIMENT ANALYSIS

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

Universal Sentence Encoder

29 Mar 2018facebookresearch/InferSent

For both variants, we investigate and report the relationship between model complexity, resource consumption, the availability of transfer task training data, and task performance.

SEMANTIC TEXTUAL SIMILARITY SENTENCE EMBEDDINGS SENTIMENT ANALYSIS SUBJECTIVITY ANALYSIS TEXT CLASSIFICATION TRANSFER LEARNING WORD EMBEDDINGS

Improving Language Understanding by Generative Pre-Training

Preprint 2018 openai/finetune-transformer-lm

We demonstrate that large gains on these tasks can be realized by generative pre-training of a language model on a diverse corpus of unlabeled text, followed by discriminative fine-tuning on each specific task.

DOCUMENT CLASSIFICATION LANGUAGE MODELLING NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC TEXTUAL SIMILARITY

A Hybrid Neural Network Model for Commonsense Reasoning

27 Jul 2019namisan/mt-dnn

An HNN consists of two component models, a masked language model and a semantic similarity model, which share a BERT-based contextual encoder but use different model-specific input and output layers.

LANGUAGE MODELLING SEMANTIC TEXTUAL SIMILARITY

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

NAACL 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