Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper
Query: Deep Text Classification Can be Fooled
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks
Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks
Deep feature weighting for naive Bayes and its application to text classification
An Improved Random Forest Classifier for Text Categorization
Few-shot learning for short text classification
A sequential algorithm for training text classifiers
Rationale-Augmented Convolutional Neural Networks for Text Classification
A scalability analysis of classifiers in text categorization
On dataless hierarchical text classification
BoosTexter: A System for Multiclass Multi-label Text Categorization
Improving text classification with word embedding
3HAN: A Deep Neural Network for Fake News Detection
Weighted Neural Bag-of-n-grams Model: New Baselines for Text Classification
Recent Trends in Text Classification Techniques
Learning Structured Representation for Text Classification via Reinforcement Learning
A Survey on Feature Selection Techniques and Classification Algorithms for Efficient Text Classification
A survey on Adversarial Attacks and Defenses in Text.
Improving binary classification on text problems using differential word features
deep unordered composition rivals syntactic methods for text classification .
Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
Simulation of Partial Discharges in Single and Double Voids Using SIMULINK
Towards object mapping in non-stationary environments with mobile robots
Convolutional networks and applications in vision
Direct Path Superfacets: An Intermediate Representation for Motion Planning
Using Network Analysis to Understand Severe Asthma Phenotypes