Sentence Classification

34 papers with code · Natural Language Processing
Subtask of Text Classification

SVM

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Greatest papers with code

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

IJCNLP 2017 brightmart/text_classification

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

SENTENCE CLASSIFICATION

Convolutional Neural Networks for Sentence Classification

EMNLP 2014 facebookresearch/pytext

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.

SENTENCE CLASSIFICATION SENTIMENT ANALYSIS

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

3 May 2018facebookresearch/InferSent

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

SENTENCE CLASSIFICATION SENTENCE EMBEDDINGS

NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning

9 Jul 2018lvapeab/nmt-keras

We present NMT-Keras, a flexible toolkit for training deep learning models, which puts a particular emphasis on the development of advanced applications of neural machine translation systems, such as interactive-predictive translation protocols and long-term adaptation of the translation system via continuous learning.

MACHINE TRANSLATION QUESTION ANSWERING SENTENCE CLASSIFICATION VIDEO CAPTIONING VISUAL QUESTION ANSWERING

Neural Semantic Encoders

EACL 2017 Smerity/keras_snli

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

MACHINE TRANSLATION NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SENTENCE CLASSIFICATION SENTIMENT ANALYSIS

Glyce: Glyph-vectors for Chinese Character Representations

NeurIPS 2019 ShannonAI/glyce

When combing with BERT, we are able to set new state-of-the-art results for a variety of Chinese NLP tasks, including language modeling, tagging (NER, CWS, POS), sentence pair classification (BQ, LCQMC, XNLI, NLPCC-DBQA), single sentence classification tasks (ChnSentiCorp, the Fudan corpus, iFeng), dependency parsing, and semantic role labeling.

DEPENDENCY PARSING IMAGE CLASSIFICATION LANGUAGE MODELLING MULTI-TASK LEARNING SEMANTIC ROLE LABELING SENTENCE CLASSIFICATION

Glyce: Glyph-vectors for Chinese Character Representations

NeurIPS 2019 ShannonAI/glyce

However, due to the lack of rich pictographic evidence in glyphs and the weak generalization ability of standard computer vision models on character data, an effective way to utilize the glyph information remains to be found.

CHINESE WORD SEGMENTATION DEPENDENCY PARSING DOCUMENT CLASSIFICATION IMAGE CLASSIFICATION LANGUAGE MODELLING MACHINE TRANSLATION MULTI-TASK LEARNING PART-OF-SPEECH TAGGING SEMANTIC ROLE LABELING SEMANTIC TEXTUAL SIMILARITY SENTENCE CLASSIFICATION SENTIMENT ANALYSIS