Search Results for author:
Found 11 papers, 8 papers with code
ClickDiffusion: Harnessing LLMs for Interactive Precise Image Editing
We demonstrate that by serializing both an image and a multi-modal instruction into a textual representation it is possible to leverage LLMs to perform precise transformations of the layout and appearance of an image.
LLM Attributor: Interactive Visual Attribution for LLM Generation
Our library offers a new way to quickly attribute an LLM's text generation to training data points to inspect model behaviors, enhance its trustworthiness, and compare model-generated text with user-provided text.
Point and Instruct: Enabling Precise Image Editing by Unifying Direct Manipulation and Text Instructions
This allows users to benefit from both the visual descriptiveness of natural language and the spatial precision of direct manipulation.
Mobile Fitting Room: On-device Virtual Try-on via Diffusion Models
The growing digital landscape of fashion e-commerce calls for interactive and user-friendly interfaces for virtually trying on clothes.
ObjectComposer: Consistent Generation of Multiple Objects Without Fine-tuning
We build upon the recent BLIP-Diffusion model, which can generate images of single objects specified by reference images.
LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked
We test LLM Self Defense on GPT 3. 5 and Llama 2, two of the current most prominent LLMs against various types of attacks, such as forcefully inducing affirmative responses to prompts and prompt engineering attacks.
ManimML: Communicating Machine Learning Architectures with Animation
A user can take a preexisting neural network architecture and easily write a specification for an animation in ManimML, which will then automatically compose animations for different components of the system into a final animation of the entire neural network.
Manifold Contrastive Learning with Variational Lie Group Operators
In this work, we propose a contrastive learning approach that directly models the latent manifold using Lie group operators parameterized by coefficients with a sparsity-promoting prior.
PrefGen: Preference Guided Image Generation with Relative Attributes
Using information from a sequence of query responses, we can estimate user preferences over a set of image attributes and perform preference-guided image editing and generation.
Oracle Guided Image Synthesis with Relative Queries
Isolating and controlling specific features in the outputs of generative models in a user-friendly way is a difficult and open-ended problem.
Visualizing Convolutional Neural Network Protein-Ligand Scoring
Here we present three methods for visualizing how individual protein-ligand complexes are interpreted by 3D convolutional neural networks.
