大模型如何给视觉模型当老师？ICML 2026探讨细粒度知识跨模态迁移，让AI理解更精准。
arXiv:2606.27527v1 Announce Type: cross Abstract: Large Language Models (LLMs) possess broad conceptual knowledge acquired through large-scale text pr…
多模态3D MRI融合局部与全局上下文，揭秘跨模态建模新思路，医学影像AI进阶必读。
arXiv:2606.26894v1 Announce Type: new Abstract: Brain MRI poses a fundamental challenge for machine learning: models must learn from high-dimensional …
统一多模态潜在扩散模型实现任意模态间的连贯生成，无需配对数据，跨模态生成能力惊艳
arXiv:2606.16408v1 Announce Type: new Abstract: We introduce MUNI, an end-to-end multimodal latent diffusion framework for any-to-any generation that …
首个多模态领域泛化基准，覆盖多种跨模态场景，助力模型稳健性评估。
arXiv:2606.00891v1 Announce Type: new Abstract: Multi-modal Domain Generalization (MMDG) seeks to leverage complementary modalities to enhance model r…
顶会ICML 2026提出多模态融合新方法，利用自一致性任务梯度场实现高效跨模态交互。
arXiv:2410.15475v2 Announce Type: replace Abstract: Multimodal learning aims to preserve as much task-related information as possible from different i…
统一多模态理解与生成框架，唤醒空间智能，为AI视觉注入全新维度。
arXiv:2605.04128v2 Announce Type: replace-cross Abstract: We present JoyAI-Image, a unified multimodal foundation model for visual understanding, text…