Representation Learning
Fine-tuning LLM-based text embedders via contrastive learning maps inputs and outputs into a new representational space, discarding the …
Information retrieval is a core component of many intelligent systems as it enables conditioning of outputs on new and large-scale …
Information retrieval is a core component of many intelligent systems as it enables conditioning of outputs on new and large-scale …
Applications such as disaster management enormously benefit from rapid availability of satellite observations.
Traditionally, data …
We study settings where gradient penalties are used alongside risk minimization with the goal of obtaining predictors satisfying …
This work introduces a novel principle we call disentanglement via mechanism sparsity regularization, which can be applied when the …
Contrastive self-supervised learning has emerged as a promising approach to unsupervised visual representation learning. In general, …