Machine learningDeep learning / NLP / CV
多模态句子嵌入
多模态句子嵌入将文本和图像（有时也包括音频或视频）映射到一个共享的连续向量空间中，使得来自不同模态的语义相关对彼此靠近。通过在大型配对语料库上进行对比目标训练，这些表示支持跨模态检索、零样本分类和视觉-语言推理。
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来源
- Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., ... & Sutskever, I. (2021). Learning transferable visual models from natural language supervision. In Proceedings of the 38th International Conference on Machine Learning (ICML), pp. 8748–8763. PMLR. link ↗
- Frome, A., Corrado, G. S., Shlens, J., Bengio, S., Dean, J., Ranzato, M., & Mikolov, T. (2013). DeViSE: A deep visual-semantic embedding model. In Advances in Neural Information Processing Systems (NeurIPS), Vol. 26. link ↗
如何引用本页
ScholarGate. (2026, June 3). Multimodal Sentence Embeddings (Joint Vision-Language Representation Learning). ScholarGate. https://scholargate.app/zh/deep-learning/multimodal-sentence-embeddings
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