vision capabilitiesRecent studies investigated the potential of large language models (LLMs) for clinical decision making and answering exam questions based on text input. Recent developments of LLMs have extended these models with vision capabilities. These image processing LLMs are called vision-...
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...
Recently, Vision Large Language Models (VLLMs) integrated with vision encoders have shown promising performance in vision understanding. The key of VLLMs is to encode visual content into sequences of visual tokens, enabling VLLMs to simultaneously process both visual and textual content. However, ...
Large Vision-Language Model 通常LVLM包含⼀个视觉编码器、⼀个⽂本编码器和⼀个跨模态的对⻬⽹络。 LVLMs的训练通常由三部分组成: 视觉和⽂本编码器在⼤规模单模态数据集上分别进⾏预训练。 将这两个编码器通过视觉⽂本对⻬预训练进⾏对⻬,这可以使得LLM为给定图像⽣成有意义的描述。
In this work, we leverage the ability to convert procedural materials into standard Python programs and fine-tune a large pre-trained vision-language model (VLM) to generate such programs from input images. To enable effective fine-tuning, we also contribute an open-source procedural material ...
This paper evaluates the current state of vision-based large language models in the domains of intuitive physics, causal reasoning and intuitive psychology. Through a series of controlled experiments, we investigate the extent to which these modern models grasp complex physical interactions, causal ...
《MiniGPT-4: Enhancing Vision-language Understanding with Advanced Large Language Models》论文学习 最新的GPT-4展示了非凡的多模态能力,例如直接从手写文本生成网站和识别图像中的幽默元素。这些特性在以往的视觉-语言模型中很少见。然而,GPT-4背后的技术细节仍然未公开。我们认为,GPT-4增强的多模态生成能力源自于...
Libra: Building Decoupled Vision System on Large Language Models ICML 2024-05-16 Github Local Demo CuMo: Scaling Multimodal LLM with Co-Upcycled Mixture-of-Experts arXiv 2024-05-09 Github Local Demo How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Sourc...
agent-based simulation with large language models, the first step is to construct the environment, virtual or real, and then design how the agent interacts with the environment and other agents. Thus, we need to propose proper methods for an environment that LLM can perceive and interact with....
Multimodal Large Language Models (MLLM) have recently achieved impressive performance on vision-language tasks ranging from visual question-answering and image captioning to visual reasoning and image generation. However, when prompted to identify or count (perceive) the entities in a given image, ...