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LEPARD: Learning Explicit Part Discovery for 3D Articulated Shape Reconstruction Di Liu Qilong Zhangli Y unhe Gao Dimitris N. Metaxas Rutgers University
Reconstructing the 3D articulated shape of an animal from a single in-the-wild image is a challenging task.
SafeLoRA:theSilverLiningofReducingSafety RiskswhenFine-tuningLargeLanguageModels
It is worth noting thatSafe LoRAis a training-free and data-free approach, as it only requires the knowledge of the weights from the base and aligned LLMs.
CoresetforLine-SetsClustering
A natural generalization is to replace this input setP of n points by a setP of n sets inX. The distance from such an input setP P to a setC of centers can then be defined as the distance between the closest point-center pair. This problem is calledk-mean for sets; see e.g.
CoresetforLine-SetsClustering
A natural generalization is to replace this input setP of n points by a setP of n sets inX. The distance from such an input setP P to a setC of centers can then be defined as the distance between the closest point-center pair. This problem is calledk-mean for sets; see e.g.
High-Fidelity Audio Compression with Improved RVQGAN
Language models have been successfully used to model natural signals, such as images, speech, and music.
SupplementaryMaterials
Further,inthemiddlestage,i.e. fromthe7thto9thlayers,head tokens draw more attention from other tokens.