Natural Language Processing (53)
- A Convolutional Neural Network for Modelling Sentences
- A New Method of Region Embedding for Text Classification
- A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification
- A statistical interpretation of term specificity and its application in retrieval
- ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs
- Attentional Encoder Network for Targeted Sentiment Classification
- CHARAGRAM: Embedding Words and Sentences via Character n-grams
- Character-Based Parsing with Convolutional Neural Network
- Character-level Convolutional Networks for Text Classification
- Character-level Intra Attention Network for Natural Language Inference
- Component-Enhanced Chinese Character Embeddings
- Context-Dependent Sentiment Analysis in User-Generated Videos
- Convolutional Neural Networks for Sentence Classification
- Convolutional Neural Networks for Text Categorization: Shallow Word-level vs. Deep Character-level
- Convolutional Sequence to Sequence Learning
- Deconvolutional Paragraph Representation Learning
- Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts
- Deep Learning applied to NLP
- Dependency-based Convolutional Neural Networks for Sentence Embedding
- Dilated Recurrent Neural Networks
- Distributed Representations of Words and Phrases and their Compositionally
- DropAttention: A Regularization Method for Fully Connected Self Attention-Networks
- Dropout Training as Adaptive Regularization
- Effective Use of Word Order for Text Categorization with Convolutional Neural Networks
- Explaining Word Embeddings via Disentangled Representation
- From Small-scale to Large-scale Text Classification
- Glyph-aware Embedding of Chinese Characters
- Hierarchical Attention Networks for Document Classification
- How Large Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection
- Interpretable Adversarial Training for Text
- Joint Embedding of Words and Labels for Text Classification
- Language Modeling with Gated Convolutional Networks
- Large Scale Multi-Label Text Classification with Semantic Word Vectors
- Learning Character-level Compositionality with Visual Features
- Learning Character-level Representations for Part-of-Speech Tagging
- Learning Chinese Word Representations From Glyphs Of Characters
- Learning to Compute Word Embeddings On the Fly
- Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network
- Multi-Label Neural Networks with Applications to Functional Genomics and Text Categorization
- Natural Language Processing (almost) from Scratch
- Neural Machine Translation using Bitmap Fonts
- Radical-level Ideograph Encoder for RNN-based Sentiment Analysis of Chinese and Japanese
- Saliency Learning: Teaching the Model Where to Pay Attention
- Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
- Subcharacter Information in Japanese Embeddings: When Is It Worth It?
- Text Categorization with Support Vector Machines: Learning with Many Relavant Features
- Text Classification in Asian Languages without Word Segmentation
- Tweet2Vec: Character-Based Distributed Representations for Social Media
- UNITN: Training Deep Convolutional Neural Network for Twitter Sentiment Classification
- Utilizing Visual Forms of Japanese Characters for Neural Review Classification
- Very Deep Convolutional Networks for Natural Language Processing
- Which Encoding is the Best for Text Classification in Chinese, English, Japanese and Korean?
- Word Embedding Perturbation for Sentence Classification