Veagle: Advancements in Multimodal Representation Learning

arXiv:2403.08773v1 Announce Type: new
Abstract: Lately, researchers in artificial intelligence have been really interested in how language and vision come together, giving rise to the development of multimodal models that aim to seamlessly integrate textual and visual information. Multimodal models, an extension of Large Language Models (LLMs), have exhibited remarkable capabilities in addressing a diverse array of tasks, ranging from image captioning and visual question answering (VQA) to visual grounding. While these models have showcased significant advancements, challenges persist in …

abstract aim artificial artificial intelligence arxiv capabilities cs.ai cs.cl cs.cv cs.mm development extension giving information intelligence language language models large language large language models llms multimodal multimodal models representation representation learning researchers textual together type vision visual