The 'ImageNet Moment' for LSLM Research? In the context of the flourishing development of large language models (LLMs), significant progress has been made in multimodal AI, particularly in the field ...

Abstract: In recent years, Text-to-Image (T2I) models have made remarkable advancements, yet accurate accurate association of attributes remains a key challenge. This paper presents FreeAlign, a novel ...

Recent text-to-image (T2I) generation models have advanced significantly, enabling the creation of high-fidelity images from textual prompts. However, existing evaluation benchmarks primarily focus on ...

Currently, the most dominant approach to establishing language-image alignment is to pre-train (always from scratch) text and image encoders jointly through contrastive learning, such as CLIP and its ...

Google Pixel hit the scene in 2016 and, ever since, Google has been trying to figure out how it wants to build a flagship ...

State Key Laboratory of Cognitive Neuroscience and Learning, and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China The study leverages a multimodal machine learning ...

Abstract: Image quantization is a crucial technique in image generation, aimed at learning a codebook that encodes an image into a discrete token sequence. Recent advancements have seen researchers ...