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Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation
One key challenge in Out-of-Distribution (OOD) detection is the absence of ground-truth OOD samples during training.
LLaMo: Large Language Model-based Molecular Graph Assistant
Thus, we propose LLaMo: L arge La nguage Model-based Mo lecular graph assistant, which is an end-to-end trained large molecular graph language model.
Why Transformers Need Adam: A Hessian Perspective
CNNs, MLPs, and quadratic problems, and find that SGD can perform on par with Adam on problems without block heterogeneity, but performs worse than Adam when the heterogeneity exists.
Learning Bregman Divergences with Application to Robustness
Image similarity measures are also crucial in the field of robust machine learning.
Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation
How can diffusion models process 3D geometries in a coarse-to-fine manner, akin to our multiscale view of the world?
