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Found 4 papers, 3 papers with code
The Efficiency Spectrum of Large Language Models: An Algorithmic Survey
The rapid growth of Large Language Models (LLMs) has been a driving force in transforming various domains, reshaping the artificial general intelligence landscape.
DREAM: Diffusion Rectification and Estimation-Adaptive Models
We present DREAM, a novel training framework representing Diffusion Rectification and Estimation Adaptive Models, requiring minimal code changes (just three lines) yet significantly enhancing the alignment of training with sampling in diffusion models.
Generalized Neural Collapse for a Large Number of Classes
However, most of the existing empirical and theoretical studies in neural collapse focus on the case that the number of classes is small relative to the dimension of the feature space.
Modelling the Multiwavelength Variability of Mrk 335 using Gaussian Processes
Such a reprocessing model would be characterised by lags between X-ray and optical/UV emission due to differences in light travel time.
Gaussian Processes
High Energy Astrophysical Phenomena
