用低成本探针方法预测昂贵训练效果，快速筛选3D CT视觉语言模型的最佳编码器和压缩方案。
arXiv:2607.22771v1 Announce Type: new Abstract: Picking the frozen image encoder for a 3D~CT vision--language model (VLM), together with the token-com…
新基准CORTEX专为3D胸部CT的多模态大语言模型设计，强调结构化推理而非仅看最终答案，让诊断结果可溯源至证据，提升可信度。
arXiv:2606.27264v1 Announce Type: new Abstract: Reasoning in multimodal large language models (MLLMs) has shown strong promise in medical imaging. How…
3D CT医学影像的视觉语言预训练新方法，混合视觉编码破解粗粒度语义对齐难题，助力通用医学AI。
arXiv:2606.25546v1 Announce Type: new Abstract: Vision-language pre-training (VLP) holds great promise for general-purpose medical AI by leveraging ra…
面向3D CT的视觉语言对比学习新方法，概念级对齐提升医学基础模型性能，值得关注。
arXiv:2606.24570v1 Announce Type: new Abstract: Vision-language contrastive pretraining has become the dominant recipe for 3D medical foundation model…
ICML 2026 论文提出基于 Foundation VAE 的统一框架，实现 3D CT 图像高质量重建、数据增强与生成，将推动医学影像 AI 发展。
arXiv:2605.30893v1 Announce Type: new Abstract: Variational autoencoders (VAEs) compress high resolution CT volumes into compact latents while preserv…