jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images

Andreas Koukounas; Georgios Mastrapas; Sedigheh Eslami; Bo Wang; Mohammad Kalim Akram; Michael Günther; Isabelle Mohr; Saba Sturua; Nan Wang; Han Xiao

arXiv · 2412.08802

jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images

Andreas Koukounas·Georgios Mastrapas·Sedigheh Eslami·Bo Wang·Mohammad Kalim Akram·Michael Günther·Isabelle Mohr·Saba Sturua·Nan Wang·Han Xiao

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Abstract

Contrastive Language-Image Pretraining (CLIP) has been widely used for crossmodal information retrieval and multimodal understanding tasks. However, CLIP models are mainly optimized for crossmodal vision-language tasks and underperform in single-mode text tasks. Moreover, these models are often trained on English datasets and therefore lack multilingual understanding. Additionally, from a visual understanding perspective, previous CLIP-based models exhibit insufficient understanding of visually rich documents. In this work, we propose jina-clip-v2, a contrastive vision-language model trained on text pairs, triplets and image-text pairs via a multi-task and multi-stage contrastive learning paradigm in order to support both text-only and crossmodal tasks. We employ a multilingual text encoder and expand the training dataset to include multilingual texts from 29 non-English languages, including Hindi, Chinese, German, French, and others, as well as images of visually rich documents. We evaluate the model's performance and show that jina-clip-v2 achieves notable improvements over state-of-the-art CLIP-based models in zero-shot text-only retrieval, semantic textual similarity, and crossmodal retrieval tasks in both English and multilingual settings. jina-clip-v2 also provides for flexibility in embedding dimensionality, enabling users to select the granularity of the representations. jina-clip-v2 is publicly available at https://huggingface.co/jinaai/jina-clip-v2.

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Andreas Koukounas, Georgios Mastrapas, Sedigheh Eslami, Bo Wang, Mohammad Kalim Akram, Michael Günther, Isabelle Mohr, Saba Sturua, Nan Wang, Han Xiao. 2025-04-24. jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images. https://arxiv.org/abs/2412.08802

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