4 citations · 9 across the 12 of their papers we have counts for
3 papers · 1 filter
Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations
Yongshuo Zong, Tingyang Yu, Ruchika Chavhan +2
Large language and vision-language models are rapidly being deployed in practice thanks to their impressive capabilities in instruction following, in-context learning, and so on. T…
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn
Ondrej Bohdal, Yinbing Tian, Yongshuo Zong +5
Meta-learning and other approaches to few-shot learning are widely studied for image recognition, and are increasingly applied to other vision tasks such as pose estimation and den…
Amortised Invariance Learning for Contrastive Self-Supervision
Ruchika Chavhan, Henry Gouk, Jan Stuehmer +3
Contrastive self-supervised learning methods famously produce high quality transferable representations by learning invariances to different data augmentations. Invariances establi…