1 citations · 1 across the 5 of their papers we have counts for
5 papers
Attention Alignment Between Humans and Vision-Language Models
Isaac R. Christian, Udith Haputhanthrige, Hanna Hornfeld +4
Visual perception depends on top-down goals and bottom-up sensory mechanisms. Vision-language models implement both, allowing us to treat each component as a separable hypothesis a…
Binding Visual Features Point by Point
Udith Haputhanthri, Declan Campbell, Rim Assouel +2
Despite success on standard benchmarks, vision language models display persistent failures on tasks involving processing of multi-object scenes, including many tasks that are relat…
Few-Shot Learning of Visual Compositional Concepts through Probabilistic Schema Induction
Andrew Jun Lee, Taylor Webb, Trevor Bihl +2
The ability to learn new visual concepts from limited examples is a hallmark of human cognition. While traditional category learning models represent each example as an unstructure…
Evaluating Compositional Scene Understanding in Multimodal Generative Models
Shuhao Fu, Andrew Jun Lee, Anna Wang +4
The visual world is fundamentally compositional. Visual scenes are defined by the composition of objects and their relations. Hence, it is essential for computer vision systems to…
Evidence from counterfactual tasks supports emergent analogical reasoning in large language models
Taylor Webb, Keith J. Holyoak, Hongjing Lu
We recently reported evidence that large language models are capable of solving a wide range of text-based analogy problems in a zero-shot manner, indicating the presence of an eme…