Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Neural Nets Can Learn Function Type Signatures From Binaries
Recognizing functions in binaries with neural networks
A Fast Optimization Method for General Binary Code Learning.
Symbolic Execution for Deep Neural Networks
Combining Symbolic and Function Evaluation Expressions In Neural Programs
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
BINARIZED NEURAL NETWORKS
Neural Code Comprehension: A Learnable Representation of Code Semantics
Opening the neural network black box: an algorithm for extracting rules from function approximating artificial neural networks
Binhunt: Automatically finding semantic differences in binary programs
Leveraging semantic signatures for bug search in binary programs
Training Compact Neural Networks with Binary Weights and Low Precision Activations
rev.ng: a unified binary analysis framework to recover CFGs and function boundaries
FERNN: An Algorithm for Fast Extraction of Rules from Neural Networks
BinSign: Fingerprinting Binary Functions to Support Automated Analysis of Code Executables
FINN: A Framework for Fast, Scalable Binarized Neural Network Inference
Neural network gradient-based learning of black-box function interfaces
Learning to Hash with Binary Deep Neural Network
Embedded Binarized Neural Networks
On the Computational Efficiency of Training Neural Networks
Why Deep Neural Networks for Function Approximation?
A program differencing algorithm for verilog HDL
Semantic Web-Based Seismic Disaster Management Expert System
A unified architecture for natural language processing: deep neural networks with multitask learning
Definitions related to the medical use of opioids: Evolution towards universal agreement
Spikes in Mammalian Bipolar Cells Support Temporal Layering of the Inner Retina