Stay updated with breaking news from Representation Learning. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.
Spotlight News: With deeptech becoming critical to business success, IISc's PG Level Advanced Certification programme in AI and MLOps is the right step towards buildi
TL;DR We introduce Matryoshka Representation Learning (MRL), facilitating flexible embedding sizes in vector databases. This allows a balance between efficiency and granularity. Through MRL, embeddings condense into smaller dimensions while preserving performance in retrieval and ranking tasks. In summary, MRL empowers cost-effective flexibility without compromising performance in multimodal retrieval and ranking tasks.
Deep neural networks excel at solving intuitive tasks that are hard to describe formally, such as classification, but are easily deceived by maliciously crafted samples, leading to misclassification. Recently, it has been observed that the attack-specific robustness of models obtained through adversarial training does not generalize well to novel or unseen attacks. While data augmentation through mixup in the input space has been shown to improve the generalization and robustness of models, there has been limited research progress on mixup in the latent space. Furthermore, almost no research o...
A new framework known as MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single cohesive system. The work was developed by researchers from MIT and Google.
Language models cost much more in some languages than others