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Found 8 papers, 5 papers with code
Pixel-Level BPE for Auto-Regressive Image Generation
Pixel-level autoregression with Transformer models (Image GPT or iGPT) is one of the recent approaches to image generation that has not received massive attention and elaboration due to quadratic complexity of attention as it imposes huge memory requirements and thus restricts the resolution of the generated images.
Switti: Designing Scale-Wise Transformers for Text-to-Image Synthesis
This work presents Switti, a scale-wise transformer for text-to-image generation.
Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization
Specifically, we tailor vector-based PTQ methods to recent billion-scale text-to-image models (SDXL and SDXL-Turbo), and show that the diffusion models of 2B+ parameters compressed to around 3 bits using VQ exhibit the similar image quality and textual alignment as previous 4-bit compression techniques.
Mind Your Format: Towards Consistent Evaluation of In-Context Learning Improvements
Large language models demonstrate a remarkable capability for learning to solve new tasks from a few examples.
Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics
Text-to-image generation models represent the next step of evolution in image synthesis, offering a natural way to achieve flexible yet fine-grained control over the result.
Learning to Solve Voxel Building Embodied Tasks from Pixels and Natural Language Instructions
The adoption of pre-trained language models to generate action plans for embodied agents is a promising research strategy.
Many Heads but One Brain: Fusion Brain -- a Competition and a Single Multimodal Multitask Architecture
Supporting the current trend in the AI community, we present the AI Journey 2021 Challenge called Fusion Brain, the first competition which is targeted to make the universal architecture which could process different modalities (in this case, images, texts, and code) and solve multiple tasks for vision and language.
Text Detoxification using Large Pre-trained Neural Models
We compare our models with a number of methods for style transfer.
