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Found 7 papers, 1 papers with code
Crimson: Empowering Strategic Reasoning in Cybersecurity through Large Language Models
We introduces Crimson, a system that enhances the strategic reasoning capabilities of Large Language Models (LLMs) within the realm of cybersecurity.
A comprehensive review of Quantum Machine Learning: from NISQ to Fault Tolerance
Quantum machine learning, which involves running machine learning algorithms on quantum devices, has garnered significant attention in both academic and business circles.
Long Short-Term Planning for Conversational Recommendation Systems
Specifically, the recommendation predicts the long-term recommendation target based on the conversational context and the user history.
Fundamental causal bounds of quantum random access memories
Quantum random access memory (QRAM), a fundamental component of many essential quantum algorithms for tasks such as linear algebra, data search, and machine learning, is often proposed to offer $\mathcal{O}(\log N)$ circuit depth for $\mathcal{O}(N)$ data size, given $N$ qubits.
Inductive Meta-path Learning for Schema-complex Heterogeneous Information Networks
Heterogeneous Information Networks (HINs) are information networks with multiple types of nodes and edges.
Towards provably efficient quantum algorithms for large-scale machine-learning models
Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-training and fine-tuning process.
View-Disentangled Transformer for Brain Lesion Detection
Deep neural networks (DNNs) have been widely adopted in brain lesion detection and segmentation.
