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Found 7 papers, 2 papers with code
Automated Creation of Source Code Variants of a Cryptographic Hash Function Implementation Using Generative Pre-Trained Transformer Models
Compiler optimization settings and SHA-256 hash checksums of the compiled binaries are used to cluster implementations that are equivalent but may not have identical syntax - using this clustering over 100, 000 novel and correct versions of the SHA-1 codebase were generated where each component C function of the reference implementation is different from the original code.
Automated Multi-Language to English Machine Translation Using Generative Pre-Trained Transformers
The task of accurate and efficient language translation is an extremely important information processing task.
Sampling binary sparse coding QUBO models using a spiking neuromorphic processor
We demonstrate neuromorphic computing is suitable for sampling low energy solutions of binary sparse coding QUBO models, and although Loihi 1 is capable of sampling very sparse solutions of the QUBO models, there needs to be improvement in the implementation in order to be competitive with simulated annealing.
A Robust Cybersecurity Topic Classification Tool
We also show that the majority vote mechanism of the CTC tool provides lower false negative and false positive rates on average than any of the 21 individual models.
Boolean Hierarchical Tucker Networks on Quantum Annealers
Quantum annealing is an emerging technology with the potential to solve some of the computational challenges that remain unresolved as we approach an era beyond Moore's Law.
Quantum Physics
Reducing quantum annealing biases for solving the graph partitioning problem
We first quantify the bias of the implementation of the constraint on the quantum annealer, that is, we require, in an unbiased implementation, that any two vertices have the same likelihood of being assigned to the same or to different parts of the partition.
graph partitioning
Quantum Physics
Optimizing embedding-related quantum annealing parameters for reducing hardware bias
One way to deal with these imperfections and to improve the quality of the annealing results is to apply a variety of pre-processing techniques such as spin reversal (SR), anneal offsets (AO), or chain weights (CW).
