Rectified flow learns straight-path neural ODEs for distribution transport, yielding efficient generative models and domain transfers that work well even with a single simulation step.
Generative adversarial nets
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Cross-attention control in text-conditioned models enables localized and global image edits by editing only the input text prompt.
A diffusion model variant that adds structured non-zero-mean noise via modified forward/reverse processes, yielding an ELBO loss analogous to offset noise but with time-dependent coefficients, and showing gains on synthetic high-dimensional data.
Hunyuan3D 2.0 scales flow-based diffusion transformers and texture synthesis models to generate high-resolution textured 3D assets that outperform prior state-of-the-art in geometry, alignment, and texture quality.
A structured literature survey categorizing generative AI (autoencoders, GANs, diffusion models, LLMs) and federated learning uses in IDS, covering tasks like synthetic data generation and anomaly detection plus open challenges.
citing papers explorer
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Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
Rectified flow learns straight-path neural ODEs for distribution transport, yielding efficient generative models and domain transfers that work well even with a single simulation step.
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Prompt-to-Prompt Image Editing with Cross Attention Control
Cross-attention control in text-conditioned models enables localized and global image edits by editing only the input text prompt.
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A Probabilistic Formulation of Offset Noise in Diffusion Models
A diffusion model variant that adds structured non-zero-mean noise via modified forward/reverse processes, yielding an ELBO loss analogous to offset noise but with time-dependent coefficients, and showing gains on synthetic high-dimensional data.
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Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
Hunyuan3D 2.0 scales flow-based diffusion transformers and texture synthesis models to generate high-resolution textured 3D assets that outperform prior state-of-the-art in geometry, alignment, and texture quality.
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Generative AI and Federated Learning for Intrusion Detection Systems: A Survey
A structured literature survey categorizing generative AI (autoencoders, GANs, diffusion models, LLMs) and federated learning uses in IDS, covering tasks like synthetic data generation and anomaly detection plus open challenges.