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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 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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  - **[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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