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Found 2 papers, 1 papers with code
LogPrécis: Unleashing Language Models for Automated Malicious Log Analysis
In this paper, we systematically study how to benefit from the state-of-the-art in LM to automatically analyze text-like Unix shell attack logs.
Neural combinatorial optimization beyond the TSP: Existing architectures under-represent graph structure
Recent years have witnessed the promise that reinforcement learning, coupled with Graph Neural Network (GNN) architectures, could learn to solve hard combinatorial optimization problems: given raw input data and an evaluator to guide the process, the idea is to automatically learn a policy able to return feasible and high-quality outputs.
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