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Found 5 papers, 1 papers with code
Explainable Artificial Intelligence Techniques for Software Development Lifecycle: A Phase-specific Survey
However, complex AI models, which make decisions without providing clear explanations (known as the "black-box problem"), currently restrict trust and widespread adoption of AI.
Adversarial Attacks in Multimodal Systems: A Practitioner's Survey
However, considering the vast landscape of adversarial attacks across these modalities, these models also inherit vulnerabilities of all the modalities, and ultimately, the adversarial threat amplifies.
Optimizing LLMs for Resource-Constrained Environments: A Survey of Model Compression Techniques
Large Language Models (LLMs) have revolutionized many areas of artificial intelligence (AI), but their substantial resource requirements limit their deployment on mobile and edge devices.
Gemini & Physical World: Large Language Models Can Estimate the Intensity of Earthquake Shaking from Multi-Modal Social Media Posts
Specifically, Google's Gemini models demonstrate a simplified understanding of the general relationship between earthquake magnitude, distance, and MMI intensity, accurately describing observational data even though it's not identical to established models.
SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception
SIGNet is shown to improve upon the state-of-the-art unsupervised learning for depth prediction by 30% (in squared relative error).
Ranked #71 on
Monocular Depth Estimation
on KITTI Eigen split
