Trending Research
Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models
AttendAndExcite/Attend-and-Excite
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Recent text-to-image generative models have demonstrated an unparalleled ability to generate diverse and creative imagery guided by a target text prompt.
Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
To reproduce the success of text-to-image (T2I) generation, recent works in text-to-video (T2V) generation employ large-scale text-video dataset for fine-tuning.
BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining
microsoft/biogpt
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Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain.
Ranked #1 on
Question Answering
on PubMedQA
On the Expressive Power of Geometric Graph Neural Networks
chaitjo/geometric-gnn-dojo
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The expressive power of Graph Neural Networks (GNNs) has been studied extensively through the Weisfeiler-Leman (WL) graph isomorphism test.
InstructPix2Pix: Learning to Follow Image Editing Instructions
timothybrooks/instruct-pix2pix
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We propose a method for editing images from human instructions: given an input image and a written instruction that tells the model what to do, our model follows these instructions to edit the image.
ArchiSound: Audio Generation with Diffusion
archinetai/audio-diffusion-pytorch
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The recent surge in popularity of diffusion models for image generation has brought new attention to the potential of these models in other areas of media generation.
Cut and Learn for Unsupervised Object Detection and Instance Segmentation
We propose Cut-and-LEaRn (CutLER), a simple approach for training unsupervised object detection and segmentation models.
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
salesforce/lavis
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The cost of vision-and-language pre-training has become increasingly prohibitive due to end-to-end training of large-scale models.
Ranked #1 on
Image Retrieval
on COCO
What Makes Good Examples for Visual In-Context Learning?
zhangyuanhan-ai/visual_prompt_retrieval
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To overcome the problem, we propose a prompt retrieval framework to automate the selection of in-context examples.
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
By learning the latent representations of audio signals and their compositions without modeling the cross-modal relationship, AudioLDM is advantageous in both generation quality and computational efficiency.
