4 papers · 1 filter
Traversing the Satisfaction-Diversity Frontier in Text-to-Image Diffusion
Kevin Zhai, Siva Rajesh Kasa, Soumya Roy +2
Text-to-image generation enables users to explore several images generated from the same prompt. For these generated images to be useful, each one must reflect the user's preferenc…
Evaluating Constrained Iterative Refinement for Scalable Vector Graphics Generation with Off-the-Shelf VLMs
Matthew Perlman, James Beetham, Niels Da Vitoria Lobo +2
Scalable Vector Graphics (SVGs) power much of the modern visual ecosystem, yet state-of-the-art generative models focus almost entirely on rasterized images. We explore whether inf…
The Illusion of High Utility in Safety Alignment of Text-to-Image Diffusion Models
Adeel Yousaf, Soumik Ghosh, James Beetham +2
Safety alignment of text-to-image (T2I) diffusion models aims to suppress harmful generations while preserving utility on benign prompts. Recent methods often appear to deliver hig…
OmniToM: Benchmarking Theory of Mind in LLMs via Explicit Belief Modeling
Adam Bawatneh, Sagar Sapkota, Amrit Singh Bedi +2
Theory of Mind (ToM), the ability to infer others' knowledge, intentions, and emotions, is commonly evaluated in large language models (LLMs) using end-point question answering, wh…