90 citations · 98 across the 3 of their papers we have counts for
3 papers
Improving fine-grained understanding in image-text pre-training
Ioana Bica, Anastasija Ilić, Matthias Bauer +8
We introduce SPARse Fine-grained Contrastive Alignment (SPARC), a simple method for pretraining more fine-grained multimodal representations from image-text pairs. Given that multi…
A Generalist Neural Algorithmic Learner
Borja Ibarz, Vitaly Kurin, George Papamakarios +12
The cornerstone of neural algorithmic reasoning is the ability to solve algorithmic tasks, especially in a way that generalises out of distribution. While recent years have seen a…
emoji2vec: Learning Emoji Representations from their Description
Ben Eisner, Tim Rocktäschel, Isabelle Augenstein +2
Many current natural language processing applications for social media rely on representation learning and utilize pre-trained word embeddings. There currently exist several public…