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...
Title: HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation Paper:arxiv.org/pdf/2502.0983 Code:github.com/DCDmllm/Heal 文章摘要 我们提出了HealthGPT,一个强大的医学大型视觉语言模型(Med-LVLM),它将医学视觉理解和生成能力集成在一...
foundationgptlanguage-modelmultimodalmulti-modalityvision-transformergpt-4visual-language-learningllmchatgptinstruction-tuninglarge-language-modelsupervised-finetuningmllmvision-language-modellarge-vision-language-model UpdatedJan 22, 2025 Python PKU-YuanGroup/MoE-LLaVA ...
Can large vision-language models (LVLMs) learn from natural language feedback to improve their alignment and interaction ability? Excited to share DRESS, an LVLM trained via natural language feedback. Paper:https://t.co/UB1pdaN4q1 Dataset:https://t...
We believe large vision–language models have great potential to address this need. However, applying off-the-shelf large models directly in medical scenarios normally provides unsatisfactory results.In this work, we present MammoVLM, a large vision–language model to assist patients with problems ...
《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...
“A simple and effective pruning approach for large language models.”, arXiv:2306.11695 (2023). [3] Touvron, Hugo, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou. “Training data-efficient image transformers & d...
DRIVEVLM: The Convergence of Autonomous Driving and Large Vision-Language Models DriveVLM 时间:24.02 机构:Tsinghua University && Li Auto TL;DR 当前自动驾驶落地的主要难点是解决各种长尾的复杂路况。本文提出DriveVLM算法,利用VLM来增强智驾的场景描述、场景分析、层级规划能力,同时为了克服VLM计算量大的问题,又...
Few-shot classification (FSC) is a fundamental yet challenging task in computer vision that involves recognizing novel classes from limited data. While previous methods have focused on enhancing visual features or incorporating additional modalities, Large Vision Language Models (LVLMs) offer a promising...
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 ...