activity
20192026
most citedDifferentiable Drawing and Sketching

9 citations · 30 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CL2026

Calibrated Ambiguity in Multimodal Language Models: Humans reach for cultural references, while models describe the picture

Cody Kommers, Mingrui Ye, Evelyn Gius +4

Ambiguity is often treated as a bug for AI systems to resolve---but in human communication and culture, ambiguity can also be a generative resource. From humour to politics to art,…

cs.AI2026★ 4 cited

Computational Hermeneutics: Evaluating generative AI as a cultural technology

Cody Kommers, Ruth Ahnert, Maria Antoniak +35

Generative AI systems are increasingly recognized as cultural technologies, yet current evaluation frameworks often treat culture as a variable to be measured rather than fundament…

cs.RO2022

Physically Embodied Deep Image Optimisation

Daniela Mihai, Jonathon Hare

Physical sketches are created by learning programs to control a drawing robot. A differentiable rasteriser is used to optimise sets of drawing strokes to match an input image, usin…

cs.LG2021

Shared Visual Representations of Drawing for Communication: How do different biases affect human interpretability and intent?

Daniela Mihai, Jonathon Hare

We present an investigation into how representational losses can affect the drawings produced by artificial agents playing a communication game. Building upon recent advances, we s…

cs.CV2021★ 5 cited

Learning to Draw: Emergent Communication through Sketching

Daniela Mihai, Jonathon Hare

Evidence that visual communication preceded written language and provided a basis for it goes back to prehistory, in forms such as cave and rock paintings depicting traces of our d…

cs.CV2021★ 9 cited

Differentiable Drawing and Sketching

Daniela Mihai, Jonathon Hare

We present a bottom-up differentiable relaxation of the process of drawing points, lines and curves into a pixel raster. Our approach arises from the observation that rasterising a…