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title: README |
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# VLM2Vec & MMEB: Benchmarking multimodal embeddings and adapting state-of-the-art multimodal large language models into embedding models. |
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- **Website** - https://tiger-ai-lab.github.io/VLM2Vec/ |
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- **Github** https://github.com/TIGER-AI-Lab/VLM2Vec |
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## List of Our Papers |
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### Main VLM2Vec / MMEB Series |
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- **[VLM2Vec / MMEB](https://arxiv.org/pdf/2410.05160)** – Image embedding benchmarking and models. (ICLR2025) |
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- **[VLM2Vec-V2 / MMEB-V2](https://arxiv.org/pdf/2507.04590)** – Extension of our previous work to video and visual document tasks. (TMLR2026) |
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### Other Related Papers from Our Team |
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- **[GAE-Retriever](https://arxiv.org/pdf/2506.22056)** – Benchmark and model for trajectory modeling in GUI environments. (Computer-use Agents@ICML 2025) |
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- **[B3](https://arxiv.org/pdf/2505.11293)** – A novel batch mining strategy for contrastive learning. (Neurips2025) |
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