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Collections including paper arxiv:2401.09865

about 15 hours ago

DocLLM: A layout-aware generative language model for multimodal document understanding

Paper • 2401.00908 • Published Dec 31, 2023 • 177
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training

Paper • 2401.00849 • Published Jan 1 • 14
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents

Paper • 2311.05437 • Published Nov 9, 2023 • 42
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing

Paper • 2311.00571 • Published Nov 1, 2023 • 40

generation-diffusion

High-Quality Image Restoration Following Human Instructions

Paper • 2401.16468 • Published Jan 29 • 12
Object-Driven One-Shot Fine-tuning of Text-to-Image Diffusion with Prototypical Embedding

Paper • 2401.15708 • Published Jan 28 • 10
Taiyi-Diffusion-XL: Advancing Bilingual Text-to-Image Generation with Large Vision-Language Model Support

Paper • 2401.14688 • Published Jan 26 • 13
TIP-Editor: An Accurate 3D Editor Following Both Text-Prompts And Image-Prompts

Paper • 2401.14828 • Published Jan 26 • 7

YOLO-World: Real-Time Open-Vocabulary Object Detection

Paper • 2401.17270 • Published Jan 30 • 32
Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities

Paper • 2401.14405 • Published Jan 25 • 11
Improving fine-grained understanding in image-text pre-training

Paper • 2401.09865 • Published Jan 18 • 15
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data

Paper • 2404.15653 • Published Apr 24 • 26

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 140
Improving fine-grained understanding in image-text pre-training

Paper • 2401.09865 • Published Jan 18 • 15

Note for some newest papers

DiffusionGPT: LLM-Driven Text-to-Image Generation System

Paper • 2401.10061 • Published Jan 18 • 27
Improving fine-grained understanding in image-text pre-training

Paper • 2401.09865 • Published Jan 18 • 15

about 3 hours ago

Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis

Paper • 2401.09048 • Published Jan 17 • 8
Improving fine-grained understanding in image-text pre-training

Paper • 2401.09865 • Published Jan 18 • 15
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Paper • 2401.10891 • Published Jan 19 • 58
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild

Paper • 2401.13627 • Published Jan 24 • 71

Text to Image Papers

ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations

Paper • 2312.04655 • Published Dec 7, 2023 • 20
FreeControl: Training-Free Spatial Control of Any Text-to-Image Diffusion Model with Any Condition

Paper • 2312.07536 • Published Dec 12, 2023 • 16
Clockwork Diffusion: Efficient Generation With Model-Step Distillation

Paper • 2312.08128 • Published Dec 13, 2023 • 12
CLIP as RNN: Segment Countless Visual Concepts without Training Endeavor

Paper • 2312.07661 • Published Dec 12, 2023 • 16

De-Diffusion Makes Text a Strong Cross-Modal Interface

Paper • 2311.00618 • Published Nov 1, 2023 • 21
The Chosen One: Consistent Characters in Text-to-Image Diffusion Models

Paper • 2311.10093 • Published Nov 16, 2023 • 56
Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model

Paper • 2311.13231 • Published Nov 22, 2023 • 26
Diffusion Model Alignment Using Direct Preference Optimization

Paper • 2311.12908 • Published Nov 21, 2023 • 47

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