196 citations · 269 across the 12 of their papers we have counts for
6 papers · 1 filter
MetaCLUE: Towards Comprehensive Visual Metaphors Research
Arjun R. Akula, Brendan Driscoll, Pradyumna Narayana +9
Creativity is an indispensable part of human cognition and also an inherent part of how we make sense of the world. Metaphorical abstraction is fundamental in communicating creativ…
PaLI: A Jointly-Scaled Multilingual Language-Image Model
Xi Chen, Xiao Wang, Soravit Changpinyo +26
Effective scaling and a flexible task interface enable large language models to excel at many tasks. We present PaLI (Pathways Language and Image model), a model that extends this…
PreSTU: Pre-Training for Scene-Text Understanding
Jihyung Kil, Soravit Changpinyo, Xi Chen +4
The ability to recognize and reason about text embedded in visual inputs is often lacking in vision-and-language (V&L) models, perhaps because V&L pre-training methods have often f…
MaXM: Towards Multilingual Visual Question Answering
Soravit Changpinyo, Linting Xue, Michal Yarom +5
Visual Question Answering (VQA) has been primarily studied through the lens of the English language. Yet, tackling VQA in other languages in the same manner would require a conside…
All You May Need for VQA are Image Captions
Soravit Changpinyo, Doron Kukliansky, Idan Szpektor +3
Visual Question Answering (VQA) has benefited from increasingly sophisticated models, but has not enjoyed the same level of engagement in terms of data creation. In this paper, we…
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks
Nan Ding, Xi Chen, Tomer Levinboim +2
With the increasing abundance of pretrained models in recent years, the problem of selecting the best pretrained checkpoint for a particular downstream classification task has been…