Sentence Classification

104 papers with code • 6 benchmarks • 14 datasets

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Libraries

Use these libraries to find Sentence Classification models and implementations

Most implemented papers

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

google-research/bert NAACL 2019

We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers.

Convolutional Neural Networks for Sentence Classification

PaddlePaddle/PaddleNLP EMNLP 2014

We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks.

A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification

brightmart/text_classification IJCNLP 2017

Convolutional Neural Networks (CNNs) have recently achieved remarkably strong performance on the practically important task of sentence classification (kim 2014, kalchbrenner 2014, johnson 2014).

BioBERT: a pre-trained biomedical language representation model for biomedical text mining

dmis-lab/biobert 25 Jan 2019

Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows.

PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts

Franck-Dernoncourt/pubmed-rct IJCNLP 2017

First, the majority of datasets for sequential short-text classification (i. e., classification of short texts that appear in sequences) are small: we hope that releasing a new large dataset will help develop more accurate algorithms for this task.

What you can cram into a single vector: Probing sentence embeddings for linguistic properties

facebookresearch/SentEval 3 May 2018

Although much effort has recently been devoted to training high-quality sentence embeddings, we still have a poor understanding of what they are capturing.

Neural Networks for Joint Sentence Classification in Medical Paper Abstracts

vishalrk1/SkimLit EACL 2017

Existing models based on artificial neural networks (ANNs) for sentence classification often do not incorporate the context in which sentences appear, and classify sentences individually.

SciBERT: A Pretrained Language Model for Scientific Text

allenai/scibert IJCNLP 2019

Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive.

Neural Semantic Encoders

tsendeemts/nse EACL 2017

We present a memory augmented neural network for natural language understanding: Neural Semantic Encoders.

Character-level and Multi-channel Convolutional Neural Networks for Large-scale Authorship Attribution

asad1996172/Authorship-attribution-using-CNN 21 Sep 2016

Convolutional neural networks (CNNs) have demonstrated superior capability for extracting information from raw signals in computer vision.