Machine learning methodologies encompass algorithmic frameworks and architectures for training, optimizing, and deploying models such as neural networks, transformers, diffusion models, and reinforcement learning agents. Work in this area develops new training objectives, curriculum schemes, speculative and efficient decoding, pruning and communication-reduction strategies, and biologically inspired or physics-informed architectures. The domain also includes safety preservation, unlearning, scaling laws, and specialized methods for vision, language, control, and scientific computing, aiming to improve performance, efficiency, robustness, and controllability of complex AI systems.
Computer Sciences
Although AI is not intentionally biased, it can inherit biases from the data fed into it, learning and repeating them until the system becomes inherently unfair. This is complicated by the problem of identifying where the ...
Apr 2, 2026
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Security
From smartphone facial recognition to autonomous vehicles, artificial intelligence (AI) has long been protected as a black box. However, a joint research team from KAIST and international institutions has uncovered a new ...
Apr 1, 2026
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Computer Sciences
The number of scientific papers is growing so rapidly that scientists are no longer able to keep track of all of them, even in their own research area. Researchers from the Karlsruhe Institute of Technology (KIT), in collaboration ...
Apr 1, 2026
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Engineering
Electrochemical deposition, or electroplating, is a common industrial technique that coats materials to improve corrosion resistance and protection, durability and hardness, conductivity and more. A Los Alamos National Laboratory ...
Apr 1, 2026
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Security
Oak Ridge National Laboratory's Center for Artificial Intelligence Security Research (CAISER) is shining a light on AI vulnerabilities. While AI models offer tremendous economic, humanitarian and national security potential, ...
Mar 28, 2026
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Robotics
What if technology, such as self-driving cars, drones, or intelligent navigation systems, could understand the world the way we do—not just seeing shapes, but recognizing meaning? A person waiting at a crosswalk, a bicycle ...
Mar 26, 2026
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Computer Sciences
Capturing a picturesque scene through reflective materials, such as glass, often results in an unintended superimposition—showing both the transmitted scene and the undesired reflected scene. While traditional reflection ...
Mar 26, 2026
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Software
Typically, AI requires massive amounts of training data to understand complex human actions. However, in real-world scenarios, it is often difficult to secure sufficient video data for specific actions. A research team led ...
Mar 26, 2026
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Hardware
Researchers have developed a holographic data storage approach that stores and retrieves information in three dimensions by combining three properties of light—amplitude, phase and polarization. By allowing more data to be ...
Mar 26, 2026
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Engineering
Researchers introduce a novel generative AI-driven framework, MMCN (Memory-aware Multi-Conditional generation Network), for forecasting future urban layouts by jointly considering building density, building height, transportation ...
Mar 24, 2026
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