Foundation AI models offer knowledge that spans the internet, but they generally lack an understanding of proprietary business data and processes.

Google’s Carolina Parada says Gemini has enabled huge robotics breakthroughs, like the new on-device AI.

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Unsupervised domain adaptation (UDA) aims to adapt models learned from a well-annotated source domain to a target domain, where only unlabeled samples are available. To this end, adversarial training ...

Fine-tuning stands out as an emerging trend in recent machine learning systems, offering significant utility across domains from transfer learning, large language models to privacy-sensitive tasks on ...

TL;DR This paper introduces SparseLoRA, a method that uses contextual sparsity to accelerate LLM fine-tuning, cutting compute by up to $\mathbf {2.2\times}$ and runtime by $\mathbf {1.6\times}$ while ...

Feature Tuning Mixup (FTM) This repository is the official PyTorch implementation of the paper: Improving Transferable Targeted Attacks with Feature Tuning Mixup (CVPR 2025).