Sentence Classification
99 papers with code • 6 benchmarks • 14 datasets
Benchmarks
These leaderboards are used to track progress in Sentence Classification
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Libraries
Use these libraries to find Sentence Classification models and implementationsDatasets
Pubmed
SciCite
PubMed RCT
PcMSP
E2E Refined
Cards Against Humanity
Most implemented papers
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
google-research/bert
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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
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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
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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
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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
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
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
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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
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IJCNLP 2019
Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive.
Neural Semantic Encoders
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
Convolutional neural networks (CNNs) have demonstrated superior capability for extracting information from raw signals in computer vision.
