Papers
Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors Paid Members Public
QA4RE is a framework that aligns RE with question answering (QA). It enables LLMs to outperform strong zero-shot baselines by a large margin. This work illustrates a promising way of adapting LLMs to challenging tasks by aligning these tasks with more common instruction-tuning tasks like QA.
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold Paid Members Public
This paper explores a new way of controlling GANs that includes "dragging" any points of the image to reach target points in a user-interactive manner - DragGAN. It can help to deform an image with precise control over where pixels go, thus manipulating the pose, shape, expression, etc.
Segment Anything Model Paid Members Public
SAM is a promptable segmentation system with zero-shot generalization to unfamiliar objects and images, without the need for additional training. The model was trained on Meta AI’s SA-1B dataset for 3-5 days on 256 A100 GPUs. Make sure that you try it!
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects Paid Members Public
BundleSDF is a near real-time method for 6-DoF tracking of an unknown object from a monocular RGBD video sequence, while performing neural 3D reconstruction of the object. The method significantly outperforms existing approaches.
Neural Preset for Color Style Transfer Paid Members Public
Neural Preset is a technique that uses AI to generate and transfer color styles. It can extract color styles from given reference images, store them as presets, and apply them to other images and videos, producing output with target color styles. Check it out!
BloombergGPT: A Large Language Model for Finance Paid Members Public
BloombergGPT is a 50 billion parameter language model that is trained on a wide range of financial data. It is validated on standard LLM benchmarks, open financial benchmarks, and a suite of internal benchmarks that most accurately reflect our intended usage.
S-NeRF: Neural Radiance Fields for Street Views Paid Members Public
In this paper, the authors propose a new street-view NeRF (S-NeRF) that considers novel view synthesis of both the large-scale background scenes and the foreground moving vehicles jointly. Learn more about their approach and the results of experiments!
Universal Guidance for Diffusion Models Paid Members Public
Typical diffusion models cannot be conditioned on other modalities without retraining. This work presents a universal guidance algorithm that enables diffusion models to be controlled by arbitrary guidance modalities without the need to retrain any use-specific components.
