Vision-capable large language models cannot effectively use images to increase performance on radiology board-style examination questions. When using textual data alone, Claude 3.5 Sonnet outperforms GPT-4V and Gemini 1.5 Pro, highlighting the advancements in the field and its potential for use in fu...
LVLM(Large Vision-Language Models)中的幻觉问题是指模型生成的文本内容与实际视觉输入之间存在不一致性。为了缓解这一问题,研究者们提出了多种方法,这些方法主要针对幻觉产生的原因进行优化。以下是一些关键的缓解策略: 数据优化:通过改进训练数据来减轻幻觉。 偏见缓解(Bias Mitigation):通过使用对比性指令调整(CIT)和...
0x3:Training https://github.com/Vision-CAIR/MiniGPT-4/blob/main/MiniGPT4_Train.md 参考链接: https://huggingface.co/Vision-CAIR/vicuna-7bhttps://github.com/Vision-CAIR/MiniGPT-4/blob/main/minigpt4/configs/models/minigpt4_vicuna0.yaml#L18https://drive.google.com/file/d/1RY9jV0dyqLX-...
吴恩达《使用LlamaIndex构建主动式RAG|Building Agentic RAG with LlamaIndex》中英字幕 吴恩达《深入模型量化|Quantization in Depth》中英字幕 【英文可关,可拖拽】吴恩达《视觉模型的提示工程|Prompt Engineering for Vision Models》中英字幕 吴恩达《Mistral入门|Getting Started with Mistral》中英字幕 吴恩达《Hugging Fac...
[2304.10592] MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models (arxiv.org) 模型结构: MiniGPT-4的模型结构 MiniGPT-4的模型结构是在BLIP-2的基础上,在Q-Former之后加了一个线形层。这个线性层的作用也是将Q-Former输出的visual feature和LLM输入端的linguistic space做一...
Large language models (LLMs) have notably accelerated progress towards artificial general intelligence (AGI), with their impressive zero-shot capacity for user-tailored tasks, endowing them with immense potential across a range of applications. However, in the field of computer vision, despite the ...
大规模视觉-语言模型(Large Vision-Language Models,LVLMs)基本上使用得都是同一个视觉词表——CLIP,它也适用于大部分的视觉任务。但是,对于一些特殊的任务往往需要更密集和更细致的感知,比如文档OCR和图标理解,特别是对于非英语场景,CLIP的词表在分词时往往比较低效,并且还可能会遇到无法分词的问题。基于此问题,作者...
Enhancing Multimodal Large Language Models with Vision Detection Models: An Empirical Study arXiv 2024-01-31 Coming soon - MoE-LLaVA: Mixture of Experts for Large Vision-Language Models arXiv 2024-01-29 Github Demo InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension...
Some noteworthy examples of such tools include generative AI-based large language models (LLMs) such as generative pretrained transformer 3.5 (GPT 3.5), generative pretrained transformer 4 (GPT-4), and Bard. LLMs are versatile and effective for various tasks such as composing poetry, writing ...
a robot should take, they are still limited only to guessing when placed in unfamiliar environments. Therefore, although we use ungrounded language-only models in our evaluation, we expect that our method could be combined with vision-language models easily, and would provide complementary benefits....