VLM和VLP都是多模态中对视觉和语言信息进行处理,其中很大一部分是相同,因此,在阅读VLM之前,可以先阅读MaWB:VLP(视觉语言预训练)这篇文章,其中的一些方法,比如CLIP,也是VLM中非常重要的方法。 其他一些概述性文章如下: ● Vision-Language Models for Vision Tasks: A Survey(2023年) ● Guide to Vision-Language ...
VLM，即视觉语言模型，专注于处理视觉与语言信息，旨在实现跨模态的理解与生成。在阅读VLM之前，了解VLP（视觉语言预训练）的相关方法，比如CLIP，会非常有益。CLIP等技术在VLM中扮演重要角色。多模态领域的概述性文章提供了对VLM的深入洞察，包括《Vision-Language Models for Vision Tasks: A Survey（2023...
最近在Visual-Language Model(缩写VLM)任务中,prompt开始展现出强大的能力。 本文首先介绍一下prompt和fine-tuning范式本质上有什么区别,然后介绍一下NLP中基于prompt的PET和AutoPrompt方法,最后介绍一下VLM任务中应用prompt范式的CLIP和CoOp方法。 另外,CLIP和CoOp都是基于prompt的判别式VLM方法,最近还有几篇基于prompt生成...
最近在Visual-Language Model(缩写VLM)任务中,prompt开始展现出强大的能力。 本文首先介绍一下prompt和fine-tuning范式本质上有什么区别,然后介绍一下NLP中基于prompt的PET和AutoPrompt方法,最后介绍一下VLM任务中应用prompt范式的CLIP和CoOp方法。 另外,CLIP...
最近在Visual-Language Model(缩写VLM)任务中,prompt开始展现出强大的能力。 本文首先介绍一下prompt和fine-tuning范式本质上有什么区别,然后介绍一下NLP中基于prompt的PET和AutoPrompt方法,最后介绍一下VLM任务中应用prompt范式的CLIP和CoOp方法。 另外,CLIP和CoOp都是基于prompt的判别式VLM方法,最近还有几篇基于prompt...
Additionally, the next time you need to analyze an image, you could use the VLM to create descriptions for it in return. In a nutshell, the main goal of the research is to use an LLM to teach a visual language model how to understand the details from a prompt to generate more ...
a family of Visual Language Models (VLM) with this ability. Flamingo models include key architectural innovations to: (i) bridge powerful pretrained vision-only and language-only models, (ii) handle sequences of arbitrarily interleaved visual and textual data, and (iii) seamlessly ingest images or...
VLMs combine a large language model with a vision transformer, enabling complex reasoning on text and visual input. This flexibility enables VLMs to be used for a variety of use cases and can be adapted on the fly by adjusting the prompts. The VLM of choice on Jetson is VILA, given it...
image-text pairs alone are not optimal; (3) re-blending text-only instruction data to image-text data during instruction fine-tuning not only remedies the degradation of text-only tasks, but also boosts VLM task accuracy. With an enhanced pre-training recipe we build VILA, a Visual Language...
It also enjoys a smaller model size. Both settings are pre-trained on the MMC4-core dataset [zhu2023multimodal]. #Param VLM acc. (avg) #Param 0-shot 4-shot Visual Expert [wang2023cogvlm] 1.9× 67.0% 64.8% Fine-tune 1× 71.0% 72.1%Table 9: Fine-tuning LLM consistently outperforms ...