100 citations · 135 across the 24 of their papers we have counts for
5 papers · 1 filter
ObjectComposer: Consistent Generation of Multiple Objects Without Fine-tuning
Alec Helbling, Evan Montoya, Duen Horng Chau
Recent text-to-image generative models can generate high-fidelity images from text prompts. However, these models struggle to consistently generate the same objects in different co…
LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked
Mansi Phute, Alec Helbling, Matthew Hull +4
Large language models (LLMs) are popular for high-quality text generation but can produce harmful content, even when aligned with human values through reinforcement learning. Adver…
Manifold Contrastive Learning with Variational Lie Group Operators
Kion Fallah, Alec Helbling, Kyle A. Johnsen +1
Self-supervised learning of deep neural networks has become a prevalent paradigm for learning representations that transfer to a variety of downstream tasks. Similar to proposed mo…
ManimML: Communicating Machine Learning Architectures with Animation
Alec Helbling, Duen Horng Chau
There has been an explosion in interest in machine learning (ML) in recent years due to its applications to science and engineering. However, as ML techniques have advanced, tools…
PrefGen: Preference Guided Image Generation with Relative Attributes
Alec Helbling, Christopher J. Rozell, Matthew O'Shaughnessy +1
Deep generative models have the capacity to render high fidelity images of content like human faces. Recently, there has been substantial progress in conditionally generating image…