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Semantic Textual Similarity

107 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

DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

2 Oct 2019huggingface/transformers

As Transfer Learning from large-scale pre-trained models becomes more prevalent in Natural Language Processing (NLP), operating these large models in on-the-edge and/or under constrained computational training or inference budgets remains challenging.

LANGUAGE MODELLING LINGUISTIC ACCEPTABILITY NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC TEXTUAL SIMILARITY SENTIMENT ANALYSIS TRANSFER LEARNING

XLNet: Generalized Autoregressive Pretraining for Language Understanding

19 Jun 2019huggingface/transformers

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

RoBERTa: A Robustly Optimized BERT Pretraining Approach

26 Jul 2019huggingface/pytorch-transformers

Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging.

 SOTA for Question Answering on SQuAD2.0 dev (using extra training data)

LANGUAGE MODELLING LEXICAL SIMPLIFICATION NATURAL LANGUAGE INFERENCE QUESTION ANSWERING READING COMPREHENSION SEMANTIC TEXTUAL SIMILARITY SENTIMENT ANALYSIS

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

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

26 Sep 2019brightmart/albert_zh

Increasing model size when pretraining natural language representations often results in improved performance on downstream tasks.

LINGUISTIC ACCEPTABILITY NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC TEXTUAL SIMILARITY SENTIMENT ANALYSIS

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