Sentence Classification

81 papers with code • 6 benchmarks • 10 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

facebookresearch/pytext 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.

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.

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.

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.