75 citations · 372 across the 57 of their papers we have counts for
4 papers · 2 filters
Towards Visual Foundational Models of Physical Scenes
Chethan Parameshwara, Alessandro Achille, Matthew Trager +7
We describe a first step towards learning general-purpose visual representations of physical scenes using only image prediction as a training criterion. To do so, we first define "…
Prompt Algebra for Task Composition
Pramuditha Perera, Matthew Trager, Luca Zancato +2
We investigate whether prompts learned independently for different tasks can be later combined through prompt algebra to obtain a model that supports composition of tasks. We consi…
Train/Test-Time Adaptation with Retrieval
Luca Zancato, Alessandro Achille, Tian Yu Liu +3
We introduce Train/Test-Time Adaptation with Retrieval (), a method to adapt models both at train and test time by means of a retrieval module and a searchable pool of…
A Meta-Learning Approach to Predicting Performance and Data Requirements
Achin Jain, Gurumurthy Swaminathan, Paolo Favaro +8
We propose an approach to estimate the number of samples required for a model to reach a target performance. We find that the power law, the de facto principle to estimate model pe…